Double-stranded RNA (dsRNA) is a potent immunogenic impurity and its detection is a critical quality attribute in characterizing mRNA therapeutics. Standard analytical methods (e.g., sandwich ELISA) are only able to resolve the bulk presence of dsRNA and cannot characterize the different sub-species that may be present within a mRNA sample.. In this study, we use mass photometry (MP) as a single-molecule analytical platform for the simultaneous detection and characterization of dsRNA impurities in mRNA samples. We demonstrate how ionic strength can interfere with the stability of the mAb/dsRNA complex and measure the binding affinity (1 nM) under a set of parameters for reproducible characterization of the complex. We then leverage the J2 antibody to identify antibody/dsRNA complexes that then resolve dsRNA-positive species within an mRNA sample based on discrete molecular weight profiles. Furthermore, we introduce a novel MP assay that harnesses the repulsive surface chemistry of uncoated glass to exclude the bulk mRNA analyte to enable the use of higher loading concentrations to sensitively profile trace dsRNA impurities as antibody-bound species. This work establishes MP as a valuable next generation mRNA analytical tool for analyzing dsRNA byproducts within mRNA samples.
Science Journals
Course-based undergraduate research experiences (CUREs) can expand undergraduates' access to research and motivate students to stay in science. Yet, little research has examined how CURE instruction shapes student motivation. We leveraged a motivation-related characterization of non-content talk of 48 CURE and non-CURE instructors to predict the motivation-related outcomes of 462 students. We fit a series of multi-level models (MLM) in which we regressed students' post-course scientific self-efficacy, task values, scientific identity, and science-related intentions onto instructors' self-efficacy and task values-related talk, controlling for students' pre-course levels. We also fit an MLM to explore whether instructors' relationship-building talk (immediacy talk) was associated with students' rapport with their instructor. Instructors' self-efficacy talk did not affect students' self-efficacy, and instructors' immediacy talk had a marginally positive but non-significant association with students' rapport ratings. Instructors' task values talk positively influenced students' scientific identity and some but not all of their task values. Instructors' task values talk also positively influenced students' intentions to pursue a science career, but not graduate education or research careers. Collectively, these results suggest that instructors' task values talk may underpin some of the motivational effects of CURE instruction, but that task values talk need not be limited to CUREs.
Despite sharing the same genes and the same environment, individuals often develop substantial phenotypic differences. While this pattern has been documented across diverse species and traits, the processes giving rise to this 'stochastic' or non-shared environmental variation remain unclear. Recent mathematical models of development in which phenotypes are gradually constructed may offer some clues. These models show that imperfect environmental cues can generate striking variation in developmental trajectories and adult phenotypes. At the population level, such imperfect cues produce increasing stability of individual differences across ontogeny (e.g. animal personality) and patterned distributions of mature phenotypes (e.g. normal or skewed) that resemble those observed in real organisms. Our paper synthesizes existing models in which stochastic phenotypic variation arises solely as a by-product of mechanisms missing their phenotypic targets because of imperfect cues. We then link these models to related, but independent, mathematical theory exploring the environmental conditions under which stochastic phenotypic variation is favoured by natural selection. Our integration shows that stochastic sampling is often favoured over classic bet-hedging strategies involving non-plastic generalist or specialist strategies. Our findings provide new directions of research on stochastic sampling as a mechanism for adaptive stochastic variation within and across generations.
How do humans store sequences that far exceed working memory capacity? Using visuo-spatial and binary auditory sequences, we previously showed that a Language of Thought (LoT) architecture, in which simple primitives are recursively combined into hierarchical programs, enables efficient storage of structured sequences. Here we ask whether this principle extends to purely ordinal structure: sequences defined by how items repeat and in what order, as in AABBCCAABBCC, independently of their spatial content. Across three experiments, participants reproduced 12-item sequences of spatial locations with various ordinal structures. The minimal description length derived from the LoT model predicted recall accuracy with remarkable precision (r = .96), substantially outperforming Shannon entropy, Lempel-Ziv complexity, chunking models and subjective complexity ratings. Critically, fine-grained analyses of participants' inter-click intervals during reproduction revealed systematic slowdowns at the hierarchical boundaries predicted by the LoT programs, providing a behavioral signature of the underlying mental syntax. These results identify a compact vocabulary of mental primitives, repetition, mirroring, and interleaving, whose composition accounts for the symbolic compression of ordinal structures. For ordinal regularities, human sequence memory operates as a form of program induction, leveraging a domain-general capacity for hierarchical compression to encode complex structured information.
WD40 domains share a widespread {beta}-propeller fold, and often act as versatile scaffold proteins. Despite their central role in organizing dynamic cellular complexes, the molecular and structural mechanisms of many WD40 proteins remain poorly understood. Among them, DCAF7, an ubiquitously expressed and essential gene in human, also encodes a highly conserved WD40 protein in eukaryotic organisms. It is known to interact with multiple and functionally diverse partners to coordinates cellular activity of several protein kinases as well as transcriptional regulators, thereby modulating key cellular processes such as cell growth, differentiation, and transcriptional regulation. However, the precise mode of action of DCAF7 is unknown and its important divergence in sequence from better characterize WD40 prevent information transfer by similarity. Structural interactomic can reveal how protein-protein interactions (PPIs) occur within an organism and are essential for understanding biological functions and developing new therapeutic strategies. Using SLiMAn2, AlphaFold2/3 and PSSMsearch, we identified a conserved -helical short linear motif (SLiM) in several well known DCAF7 partners that binds to the top surface of its {beta}-propeller. This motif was subsequently used to generate a regular expression, to identify potential new direct binders across the DCAF7 meta-interactome and the human proteome. Domain-domain interactions were also predicted for some other partners. Finally, modeling of oligomeric complexes with such new hits reveals the structural basis of DCAF7 scaffolding, with links to neurodevelopmental disorders such as autism.
Humans comprehend language incrementally, updating the representation of sentence meaning with each incoming word. These updates are guided by the distance between each perceived word and prior expectations--the prediction error. The alignment between large language models (LLMs) and cortical activity inspires the hypothesis that the cortical computation of prediction error is Surface-based, driven by statistical patterns of word form co-occurrence. In contrast, psycholinguistic models propose that prediction error computation is Meaning-based, driven by word semantics. We used polysemic words with ambiguous semantics to distinguish these models: ambiguity would introduce uncertainty into meaning representations and hence the prediction error, if Meaning-based, but would not affect the prediction error, if Surface-based. We examined how ambiguity influenced prediction error signatures in self-paced reading times and magnetoencephalographic (MEG) neural responses during sentence processing. While an LLM-based proxy of prediction error robustly predicted reading times and neural responses to unambiguous words, it failed to predict either under ambiguity. That is, prediction error computation was altered by uncertainty in word meaning, which supports the Meaning-based model and corroborates the essential role of word meaning in predictive language processing. Our findings highlight an important limitation of LLMs as in silico models of the human language faculty.
Collagens are key components of the extracellular matrix (ECM) that play a crucial role in maintaining structure, strength, and function of the lungs. Fibrillar collagens are crosslinked by enzymes such as lysyl oxidases and transglutaminases and organized into networks by proteoglycans and glycoproteins. Collagens are the main load-bearing components and along with elastin may impart a non-linear strain hardening behavior to the lung. In disease, collagen crosslinking and organization can be disrupted, possibly due to abnormal levels of enzymes or ECM components. Few studies have examined collagen crosslinking and organization in healthy and diseased human lungs. In this study, alterations in collagen crosslinking and organization were investigated in human lung control, fibrotic and chronic obstructive pulmonary disease (COPD) tissue sections. Ultra-performance liquid chromatography and second harmonic generation microscopy measured pyridinoline crosslinks and the distribution of mature and immature collagens within the decellularized scaffolds, respectively. Fibrotic scaffolds had higher total collagen but less crosslinking per mole of collagen compared with COPD donors. Image analysis by second harmonic generation microscopy showed mature collagens populated airway or blood vessel walls in all three groups and in the parenchyma of fibrotic scaffolds. Immature collagens, on the other hand, were mainly localized to parenchymal regions in control and COPD scaffolds, with fewer immature collagens in fibrotic parenchyma. Additionally, quantification of the mature to immature collagen ratio in defined regions of control and diseased scaffolds showed increased organized collagen in fibrotic tissue. Our study shows that collagen crosslinking and organization are disrupted in fibrotic and COPD lungs and these changes may be compartment specific and can contribute to aberrant mechanical properties of diseased lungs. Our findings highlight that along with total collagen…
Conformational plasticity of RNAs plays important roles in recognizing RNA-binding proteins, and is often modulated by their binding partners. Here, we investigate RNA conformational preferences in a non-redundant dataset of 263 protein-RNA complexes to characterize the structural landscape associated with protein recognition. RNA dinucleotide segments are analyzed using seven backbone torsion angles ({delta}1, {varepsilon}1, {zeta}1, 2, {beta}2, {gamma}2, and {delta}2), two glycosidic torsion angles ({chi}1 and {chi}2) and the pseudo-torsion angle . Focusing on dinucleotide steps present in both interface and non-interface regions, we performed density-based clustering using selected backbone torsion angles to identify recurrent conformational states. We identify 28 distinct RNA dinucleotide conformers containing at least ten members each. Among these, eight conformers represent previously unreported nucleotide conformers (NtCs), including the transitional and the non-canonical states AB06, AB07, BB21, BB22, OP32, OP33, IC08 and IC09. Several of these conformers are preferentially enriched at protein-binding interfaces, suggesting their involvement in local conformational adaptation during protein-RNA recognition. The newly identified conformers span transitional A-B geometries, distorted B-like states, open conformations and compact intercalated structures, highlighting the remarkable structural plasticity of RNA in ribonucleoprotein complexes. Overall, this study expands the current understanding of RNA conformational space and provides a refined RNA dinucleotide conformer library for protein-RNA complexes. These findings will facilitate the identification of novel RNA structural motifs and improved RNA structural modeling, docking protein-RNA complexes and deep learning-based prediction frameworks for describing RNA tertiary structures.
Metatranscriptomic (MTX) sequencing enables profiling of gene expression across microbial communities, providing a framework for linking genetic potential with functional activity. However, standard pipelines report normalized abundances rather than raw counts, limiting the use of count-based RNA-seq methods, while Gaussian-based alternatives rely on transformations and assumptions that are often poorly suited to MTX data. We propose a new modeling framework for differential expression analysis of MTX data, built on a scale mixture of exponential distributions, that incorporates DNA abundance to adjust for genomic potential, accommodates subject-specific random effects, treats zeros as left-censored, and employs a mixture prior to handle extreme sparsity. Applied to the IBDMDB multi-omics cohort, differential expression results vary substantially across models, including among Gaussian approaches with different pseudocount choices. Our approach identifies a distinct subset of candidate genes not detected by existing Gaussian methods; these may provide useful leads toward a novel understanding of transcriptomic patterns associated with dysbiosis in inflammatory bowel disease. Estimated dysbiosis effect directions are consistent between our model and Gaussian-based approaches, while effect sizes from our model tend to be larger in absolute value.
Mapping the genetic basis of inter-individual heterogeneity in multifactorial diseases opens the door to mechanistic insights and opportunities for targeted intervention. In Alzheimer's disease (AD), clinical and pathological heterogeneity is well recognized, but genetic dissection is limited by a lack of well-powered cohorts with deep phenotypic characterization. Here, we introduce a polygenic score (PGS) analysis strategy to address these limitations by leveraging the inherent pleiotropy in complex trait genetics. We perform a cross-cohort, cross-trait application of pre-trained PGS, integrating 713 UK Biobank-derived PGS with 36 deep AD phenotypes across 1678 ROSMAP participants. We identify 268 statistically significant (FDR<0.1) associations between 12 prioritized PGS and 36 AD phenotypes. Prioritized PGS include blood lipid measurements, inflammatory biomarkers, and cancer traits; observed AD phenotypes include cognition, amyloid, and tangles. Of the 268 associations, 49 persist with APOE-excluded PGS. Predictive models trained on multiple prioritized PGS outperform the AD PGS or APOE alone for predicting amyloid and cognition. Lastly, our approach identifies six individual-level AD polygenic subtypes supported by distinct pathological patterns. Overall, we combine large-scale biobank resources and deeply-phenotyped cohorts using PGS, reveal genetic features underlying AD heterogeneity, and provide a general model for stratifying heterogeneous disease-focused cohorts using genomics.
Conventional diagonal stride skiing traditionally includes a glide phase, characterised by a period of relatively passive gliding on one ski. While the glide phase may take advantage of low ski-snow friction, it does not exhibit the same whole-cycle mechanical energy fluctuations seen in running or walking on foot. A new sub-technique, known as running style, substantially reduces the glide phase and may alter the role of elastic tissues, making the movement pattern more similar to uphill running on foot in its temporal organisation. We examined knee extensor and plantar flexor muscle-tendon behaviour in eight competitive skiers performing conventional diagonal and running techniques on a treadmill inclined at 10 deg. Using synchronised ultrasonography, 3D kinematics, ski forces and EMG, we quantified gastrocnemius medialis and vastus lateralis fascicle and muscle-tendon unit (MTU) dynamics in both the running (RUN) and conventional (CON) styles. Shorter glide and total cycle durations during RUN shifted MTU peak length and velocity earlier during the kick phase. Fascicles in both muscles operated at similar velocities across techniques, showing MTU-fascicle decoupling. Vastus lateralis fascicles shortened at higher absolute peak velocities than gastrocnemius in both conditions, while normalised velocities were similar. RUN increased preactivation and advanced EMG timing, while integrated EMG during the kick was lower compared to CON. These findings suggest that, despite large shifts in external mechanics between glide-based and more running-like skiing, elastic tissues may help stabilise fascicle behaviour and preserve a similar contractile strategy across muscles and techniques.
Quantifying the lipid biosynthesis rate of archaea in hot spring sediments is necessary to interpret the abundance, isotopic patterns, and environmental significance of archaeal lipid biosignatures, with implications for modern biogeochemical cycling and astrobiology. Here, we performed lipid hydrogen stable isotope probing (LH-SIP) experiments on whole sediments collected from two high-temperature, suboxic, circumneutral hot springs in Yellowstone National Park (USA) and El Tatio Geyserfield (Chile). We determined the incorporation of 2H2O into intact polar lipids (IPLs) which provides a taxon- and metabolism-agnostic quantification of biosynthesis under near-natural conditions. We targeted isoprenoid glycerol dialkyl glycerol tetraether lipids (IPL iGDGTs) and recovered structures with 0 to 7 cyclopentyl rings from both springs. We observed minor 2H-uptake into archaeal IPLs in spring sediments in Yellowstone, corresponding to decadal-scale apparent generation times (16 {+/-} 7 years), and no 2H-uptake in El Tatio sediments (consistent with minimum generation times of 35 {+/-} 5 years). We infer that net production of sedimentary IPL-iGDGTs is very slow, consistent with a combination of slow archaeal growth, persistence of older IPLs, lipid recycling, and/or contributions from recently sedimented planktonic biomass. These are the first direct, ex situ estimates of archaeal lipid production rates in terrestrial hydrothermal systems using LH-SIP incubations and provide critical constraints for interpreting archaeal lipids in ancient hot spring deposits. This research establishes a framework for assessing activity by slow-growing extremophilic archaea in hydrothermal environments and provides support for targeting hydrothermal deposits on Mars for biosignature detection efforts.
Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q=0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} 0.06, p=0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data.Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies.
Coxiella burnetii is the only member of the order Legionellales known to primarily infect vertebrates. The Q fever pathogen is also unusual in that it replicates within an acidified phagolysosome-like vacuole. The evolutionary origins of the virulence determinants underlying this lifestyle remain unclear. More broadly, little is known about how virulence-related traits arise in specialized intracellular lineages, where access to foreign-origin DNA may be more episodic. To address this question, we used Legionellales-wide comparative phylogenomics to reconstruct the gain and loss of traits affecting host interaction, immune evasion, intracellular survival, and metabolism. We found that many virulence-associated traits in C. burnetii predate the modern pathogen and were assembled stepwise in ancestors that likely occupied niches distinct from the acidified vacuolar niche of modern C. burnetii. The common ancestor shared with soft-tick Coxiella endosymbionts likely encoded most C. burnetii type IVB secretion system effectors, indicating that much of the host-manipulation repertoire in C. burnetii was already present before the emergence of the modern pathogen. Distinctive lipopolysaccharide features associated with immune evasion also appear to have accumulated progressively within the Coxiella lineage, including genes implicated in synthesis of virenose, a unique O-antigen sugar critical for C. burnetii virulence. Traits likely to support replication in the acidic Coxiella-containing vacuole likewise accumulated gradually, with generalized stress-tolerance functions predating acquisition of an Mrp cation/proton antiporter that may have further supported pH homeostasis. Additional changes in sugar transport and catabolism, glycolytic control, and respiratory metabolism may have enhanced metabolic flexibility and access to diverse substrates in this nutrient-rich niche. Together, these findings support a model in which vertebrate pathogenicity in C. burnetii emerged …
Staphylococcus aureus encounters diverse environmental conditions during colonization and infection, including fluctuations in nutrient availability, oxidative stress, and oxygen limitation. Adaptation to these environments requires regulatory systems that coordinate stress responses with metabolic remodeling. The extracytoplasmic function sigma factor SigS contributes to stress adaptation and virulence in S. aureus and directly activates expression of the sroAB operon, which encodes the small proteins SroA and SroB. While previous work demonstrated that SroA participates in feedback regulation of sigS expression, the broader physiological role of SroA has remained unclear. To define the regulatory functions of SroA, we performed RNA sequencing following inducible overexpression of sroA in S. aureus. Transcriptome analysis revealed extensive remodeling of gene expression, with approximately 200 transcripts significantly altered. Transcriptome analysis revealed coordinated repression of metabolic pathways (including nitrate respiration and nucleotide biosynthesis) alongside activation of stress-response and nutrient acquisition genes. Northern blot and quantitative RT-PCR analysis confirmed repression of narG and narJ transcripts following SroA overexpression. Consistent with these transcriptional changes, nitrate reduction assays demonstrated that SroA overexpression reduces nitrate respiration activity. In addition to repression of nitrate respiration genes, SroA overexpression broadly suppressed genes involved in de novo purine and pyrimidine biosynthesis. In contrast, transcripts associated with stress responses and nutrient acquisition, including the SOS-associated gene sosA and the phosphate transport gene pstS, were upregulated. Together, these findings identify SroA as a regulator that links stress-responsive signaling to metabolic remodeling in S. aureus, particularly through modulation of nitrate respiration pathways.