Biodiversity is commonly summarized by macroecological mean patterns, most prominently the species-area relationship (SAR) linking habitat area to expected species richness. Yet conservation, policy, and economic decisions increasingly require risk metrics: probabilities of rare but consequential biodiversity shortfalls, including local collapse. Such tail risks are central in finance and insurance but remain difficult to quantify in ecology because the data needed to estimate full richness distributions are rarely available at decision scales. Here we provide a mechanistic route from species-area relationships to biodiversity risk metrics. We show that when regional species abundances are well approximated by Fisher's log-series, a minimal immigration-extinction mechanism yields a closed-form stationary distribution for local richness whose structure tightly couples the mean SAR to richness variability and lower-tail probabilities. This coupling implies exact fluctuation-response identities and an explicit integral transform that reconstructs collapse probabilities and other tail risk measures directly from the mean SAR. These results define ecological analogues of financial risk metrics---such as collapse probability and lower-tail quantiles---without requiring direct estimation of the full richness distribution. Using high-resolution ForestGEO tree censuses spanning tropical, subtropical, and temperate forests, we find empirical support for these predictions across spatial scales. Together, our results show how widely measurable species-area relationships can be elevated from descriptive averages to operational tools for biodiversity risk assessment and reliability-based conservation planning.
Science Journals
The hippocampus is organized along dorsal-ventral and left-right axes, but whether and how these axes interact within defined neuronal populations across behavioral states remains unresolved. Here, we combined within-animal slice electrophysiology with dual-site fiber photometry to compare dorsal and ventral CA1 activity across contralateral hemispheric configurations in mice expressing CaMKII-jGCaMP8s and SynI-jRCaMP1b at distinct longitudinal sites. Ventral CA1 pyramidal neurons exhibited greater intrinsic excitability and stronger AMPAR-mediated synaptic responses than dorsal CA1 neurons. In vivo, CaMKII-defined pyramidal recordings during home cage rest revealed a left-biased event-rate asymmetry within dorsal but not ventral CA1, with no comparable asymmetry in pan-neuronal SynI recordings. Apparent dorsal-ventral differences in spontaneous event rate were therefore configuration-dependent and resolved into a hemispheric, cell-type-specific effect restricted to the CaMKII-defined population. Lead-lag analysis showed that dorsal-ventral temporal coordination was likewise reorganized across configurations and was restricted to pyramidal-cell-biased recordings. During open-field center entries, dorsal CA1 was preferentially recruited before entry across both configurations, whereas non-coordinated entries revealed a relative post-entry suppression of contralateral ventral CA1. Together, these findings suggest that dorsal-ventral CA1 organization cannot be inferred from hemisphere-pooled designs and identify a pyramidal-cell-specific left dorsal CA1 asymmetry as a structural feature that shapes both spontaneous activity and behaviorally driven recruitment along the longitudinal hippocampal axis.
Elucidating how habitat degradation facilitates extinction is critical for effective conservation efforts. Here, we propose integrating physiologically-structured population models into stochastic population viability analyses to assess how differing consequences of habitat degradation interact to drive extinction dynamics in a focal population. Using the isolated spectacled caiman Caiman crocodilus population/ecomorph from the Apaporis River as a case study, we find that threatening the resource base, which individuals increasingly rely upon, to outgrow vulnerable size ranges and mature accelerates extinction. We also found that when habitat degradation impacts both the primary adult and juvenile resource bases, this can have marked synergistic effects on threatening population viability. By contrast, destroying nesting sites has only a small effect on accelerating the impact of deteriorating prey availability. Through integrating community-level feedback between habitat degradation/change and population dynamics/structure, our approach provides a comparative framework for assessing the relative importance of distinct mechanisms through which habitat degradation ultimately drives extinction risk.
Wildlife vaccination could become a powerful strategy to mitigate disease-induced biodiversity losses, yet many vaccines for wildlife diseases provide only limited protection. Notably, tools to control the fungal pathogen Batrachochytrium dendrobatidis (Bd) are urgently needed for amphibian conservation. Laboratory experiments have demonstrated that prophylactic exposure to Bd metabolites increases host resistance, significantly reducing infection intensity in amphibians subsequently challenged with live Bd. Because Bd metabolites are non-infectious and applied topically, this treatment has potential to be administered to waterbodies to vaccinate and protect amphibians. We developed an agent-based model that indicated imperfect vaccination could reduce or amplify Bd infections at the population level, depending on degree of enhanced resistance or tolerance. Utilizing a Before-After-Control-Impact design with ten years of data, we conducted an ecosystem-level trial where we applied low levels of Bd metabolites or a sham control treatment to ponds in California and subsequently quantified Bd prevalence and infection intensity in metamorphosing Pacific chorus frogs (Pseudacris regilla). Unexpectedly, infection intensity was significantly greater in treated ponds relative to control ponds following metabolite addition. Additional model simulations indicated that this could occur via two mechanisms: (1) if treatment greatly increased tolerance alone or in combination with smaller increases in resistance, or (2) if a deleterious environmental interaction caused the treatment to increase susceptibility, rather than promote resistance. Future research is needed to determine whether tolerance or environmental factors drove heightened Bd infection intensities in this field trial to identify contexts in which this treatment can be used as a conservation tool.
Allostery enables proteins to couple environmental signals to functional outputs, yet how allosteric mechanisms diversify during evolution remains poorly understood. Here, we address this question in the ubiquitous and functionally diverse arsenic repressor (ArsR) superfamily by integrating information-theoretic bioinformatics, structural characterization of DNA recognition and NMR measurements of fast internal dynamics. We identify conserved residues that define the structural scaffold of ArsR proteins and subfamily-specific positions that encode inducer and DNA specificity. In the persulfide sensor SqrR, the crystal structure of the DNA-bound complex reveals how operator specificity is encoded by a limited set of residues, consistent with sequence-derived predictions functionally validated by in vitro transcription assays across divergent ArsR regulators. We further show that allosteric inhibition of DNA binding in SqrR occurs without large-scale conformational rearrangements and is instead associated with changes in internal dynamics, as previously observed for the zinc sensor CzrA. Together, these results support a model in which conformational entropy preserves allosteric connectivity while relaxing sequence constraints, thereby enabling functional diversification within a protein superfamily.
Genetic variation is the raw material for evolution. One source of variation is chromosomal rearrangements, which can bring genes together and form genetic linkage. Rearrangements can also suppress recombination and gene flow, as in the case of sex chromosome evolution. We conducted the first population genomic study of the red harvester ant Pogonomyrmex barbatus to investigate genomic rearrangements that differentiate the lineages J1 and J2 in the "dependent-lineage system" (also known as "social hybridogenesis"). In this unusual reproductive system, males and females from different lineages mate to create hybrids, yet these hybrids develop into sterile offspring (workers), and so the two lineages remain reproductively isolated. We sequenced high-quality reference genomes for the two lineages to search for a potential explanation of the suppression of gene flow between them. Comparison of the two genome assemblies revealed multiple large-scale genomic rearrangements, all of which occurred in the J1 lineage. The rearrangements formed some of the largest J1 chromosomes, including the largest scaffold in the assembly that was formed by at least two translocation events and additional intra-chromosomal rearrangements. The translocations brought together 118 odorant receptor (OR) genes on this rearranged chromosome, 44 of which are 9-exon ORs, which are implicated in chemical communication in ants. We also identified an enrichment of transposable elements in a large synteny gap between the translocated segments. The discovery of multiple translocations that formed large rearranged chromosomes provides a potential explanation for the reproductive isolation between the pair of dependent lineages in this system, and opens the way for the study of the molecular genetic basis of an intriguing evolutionary phenomenon in these and in other ant lineages.
Cliffs are environmentally extreme yet biodiversity-rich ecosystems that harbour specialist plants, many endemic and threatened. Plant persistence in these nutrient-poor substrates may depend on tightly linked soil- and root-associated microbial communities, which remain poorly understood. These interactions may become increasingly important with the global expansion of recreational climbing. While physical climbing impacts on vegetation are documented, potential chemical effects, from the use of climbing chalk (magnesium carbonate), on soil properties and plant-associated microbiota remain unknown. We sampled soils and roots beneath cliff-specialist and generalist plants, and unvegetated soils, across climbed and unclimbed routes in northern, central, and southern Spain. Soil physicochemical properties were quantified, fungal communities were characterized using ITS-metabarcoding, and structural equation modelling was used to disentangle direct and indirect effects. Climbing increased soil pH and altered soil chemical properties, driving shifts in fungal diversity and functional composition in soil and roots. The relative read abundance of root-associated symbiotrophic fungi declined, whereas arbuscular mycorrhizal fungi and pathogens increased in climbed cliffs. Overall effects were consistent, with cliff-specialist plants mediating nutrient and fungal shifts. Our findings show that climbing can reshape cliff soil chemistry and fungal communities, with potential cascading consequences for plant functional performance, nutrient dynamics, and ecosystem resilience.
Strong population contractions can leave a persistent genomic legacy that can influence populations long after their demographic recovery. While bottlenecks facilitate the removal of strongly deleterious mutations, the effectiveness of purging may be limited in historically small populations. The Kirtlands warbler (Setophaga kirtlandii) is a rare North American songbird with an ancestrally small population. After narrowly evading extinction, they are one of few species that have been delisted from federal protections in the USA. Despite their recovery, a previous study showed evidence for recent inbreeding and a high burden of deleterious mutations that may have not been purged despite strong bottlenecks. Historical DNA offers a unique opportunity to understand the consequences of recent demographic declines on genetic diversity. Here, we use DNA from over 100-year-old museum specimens to estimate changes in genetic load in the Kirtlands warblers pre- and post-bottleneck. We validate our results with forward-in-time genetic simulations and explore how sample size and missing data can affect estimates. Both empirical data and simulations suggest a reduced ability to purge deleterious mutations in this historically small population. Our simulations also highlight that limited sampling design and data quality can constrain the ability to detect changes.
Environmental heterogeneity across freshwater systems often promotes phenotypic variation, yet disentangling environmentally induced variation from heritable differentiation remains a central goal in evolutionary ecology. We investigated the geographic distribution and morphological differentiation, and heritability of shell traits among populations of the freshwater lymnaeid snail Pectinidens diaphanus in Patagonia. Extensive field surveys across 196 freshwater sites revealed that the species occupies a broad range of lentic and lotic habitats and constitutes the only lymnaeid inhabiting southern Patagonia. While reproductive anatomical structures were conserved across populations, shell shape differed markedly among populations from contrasting habitat types, with population identity explaining nearly 50% of total shape variation. Populations from hydrologically unstable habitats (ponds and streams) exhibited more elongated shells and relatively smaller apertures, a pattern consistent with functional responses to hydroperiod variability and desiccation risk. To assess the heritability of this differentiation, we conducted a common-garden experiment across two generations. Shell shape differences between permanent- (lagoon) and temporary- (pond) habitat-derived populations persisted into the G2 generation reared under standardized laboratory conditions, indicating that the observed variation is not solely a response to local environmental conditions but includes a heritable component. Together, our findings demonstrate that P. diaphanus constitutes the sole lymnaeid across southern Patagonia, occupying a broader range than previously documented, and that populations show heritable shell differentiation potentially associated with contrasting freshwater habitats. By integrating large-scale biogeographic surveys with morphometric and experimental approaches, this study provides new insight into how habitat variation may contribute to ecological and evolutionary di…
Ecological specialization emerges when adaptation to a focal context increases fitness in that context relative to others. Experimental evolution has been widely used to study microbial specialization in abiotic environments but not predatory specialization. Here we demonstrate evolutionary specialization by a bacterial predator and characterize associated diversification of its predation profile. Populations of the bacterium Myxococcus xanthus evolving on single, non-evolving prey species diverged in predatory performance, showing increased performance on their home prey relative to their common ancestor, and relative to foreign prey not encountered during adaptation. Adaptation to the single-prey environments resulted in striking radiation of performance profiles across a diverse panel of foreign prey that was shaped interactively by selection, chance, and indirect effects, with home-prey identity modulating the degree of stochastic indirect diversification. Despite a great diversity of indirect evolutionary effects, correlated evolution was net-positive, yielding positive predatory specialization as the general outcome. Genomic evolution mirrored phenotypic evolution in that degrees of genomic parallelism differed as a function of home-prey identity. These findings show that adaptation to even simple biotic conditions can generate great ecological and behavioral diversity, linking direct selection, deterministic indirect effects of adaptation, stochasticity, and the origins of predator specialization and diversification.
In modular organisms, where growth and fragmentation blur the boundaries between individuals, the interplay between asexual and sexual reproduction creates complex fitness trade - offs. Life - history theory predicts that resources allocated to one fitness component necessarily reduce investment in others, yet detecting these trade - offs in wild populations of clonal organisms remains challenging. Phenotypic plasticity can enhance survival, yet its influence on reproductive capacity and life - history trade - offs remains poorly understood. Using a fully crossed reciprocal transplant design, we tracked 263 colonies of the branching coral Acropora cervicornis across nine reef sites over 42 months, investigating relationships between fragmentation, morphological plasticity, and the capacity for sexual reproduction. Breakage patterns reflected both environmental and genetic factors. Primary branch breaks created a "double negative" effect - simultaneously more than doubling mortality risk and delaying attainment of a validated reproductive size class by ~40%. Conversely, higher morphological plasticity in surface area - to - volume ratio accelerated sexual maturation up to 6 - fold, counteracting the negative effects of fragmentation. In parallel, a simple demographic model parameterized with published fecundity data estimated that primary breakage reduces expected cumulative reproductive output by ~58%, a result robust across a wide range of parameter assumptions. These results demonstrate a fundamental reproductive trade-off in which asexual reproduction through fragmentation undermines sexual reproductive potential by reducing colony size. Moreover, our findings reveal that fragmentation susceptibility is broadly heritable and subject to selection, and identify a compensatory mechanism through which plasticity enhances fitness beyond immediate survival.
Birds and mammals are shrinking and shapeshifting as global temperatures rise. Ecogeographic rules predict that such changes should ease heat stress by increasing surface-area-to-volume ratios, and thus, the capacity for heat exchange. This has led to the hypothesis that body size reductions are driven by thermoregulatory selection or adaptive plasticity, although recent syntheses point to more complex, multifactorial causes. Crucially, recent theoretical models predict that thermoregulatory benefits of smaller body size only emerge at extreme deviations from average phenotypes. Here, we exploit agricultural selection in Japanese quail to directly test this hypothesis, using three breeds spanning extreme differences in body mass, surface area, and relative appendage lengths. Evaporative cooling capacity and the scope for evaporative water loss broadly followed allometric predictions when contrasting small and larger breeds. As expected, this allowed the smallest breed to tolerate higher air temperatures. However, differences in heat tolerance limits between breeds were consistently much smaller than predicted. Additionally, the breadth of thermoneutral zones overlapped in full, and upper critical temperatures were remarkably similar, between breeds. Together, these results show that heat tolerance is only weakly linked to surface-area-to-volume relationships and cannot be explained by size alone. Thus, although smaller bodies may modestly enhance heat dissipation when size variation in a population is substantial, our findings suggest that recent body size reductions and morphological shifts are unlikely to be driven primarily by thermoregulatory benefits.
Gene duplication is a major driver of evolution, yet how it generates fundamentally new molecular functions remains poorly understood. Here, we show how such novelty arose in KLMT-1, a selfish toxin that causes genetic incompatibilities in Caenorhabditis tropicalis. KLMT-1 evolved via duplication of an essential tRNA synthetase but, strikingly, lost its ancestral role in tRNA biology and translation. Instead, KLMT-1 localizes to centrosomes, where it targets Aurora kinase A (AIR-1). This innovation is mediated by a three-amino acid insertion that extends a beta-hairpin loop, enabling electrostatic interaction with a regulatory interface on the kinase. Our results demonstrate how changes in selective pressure, combined with minimal modifications in neutrally evolving regions, allow duplicated proteins to access new functional space and evolve entirely new molecular activities.
LD Score Regression (LDSC) is a prominent method, which estimates whole-genome SNP heritability from summary statistics via the slope of a linear regression of GWAS test statistics corresponding to a trait of interest against LD scores. It was claimed by the LDSC authors that the free intercept in the regression accounts for confounding bias such as population stratification. In this study, we argue that the intercept in LDSC must be fixed to 1 for accurate SNP heritability estimation. We show both theoretically and with simulations that the estimated intercept does not accurately capture population stratification effects, and that it adversely affects the accuracy of the heritability estimate introducing bias and increasing variance. Fixing the intercept to 1 eliminates bias and reduces variance when no population stratification is present. On the other hand, under population stratification, LDSC is biased with both the free and the fixed intercept. Additionally, we show that estimated standard errors in LDSC are underestimated, potentially leading to false-positives in downstream GWAS analyses.
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.
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.
Dendritic arbor morphology is shaped in part by interactions with neighboring dendrites, and its geometry strongly influences the spatial distribution and strength of synapses. These observations raise the possibility that local dendritic contacts help determine where synapses accumulate and strengthen. Previous work in cultured hippocampal neurons showed that dendrite-dendrite contact sites are non-random and associated with local synaptic clustering. Here we asked whether a different type of dendritic contact, formed between a dendrite and the soma of a neighboring neuron, behaves similarly. Using dissociated hippocampal cultures, immunofluorescence imaging, time-lapse microscopy, quantitative image analysis, stochastic spatial simulations, and minimal quantitative modeling, we identified three recurrent classes of dendrite-soma interactions (DSIs): dendrites crossing directly over a neighboring soma, growing tangentially along the soma perimeter, or contacting the proximal region where a neighboring dendrite emerges from the soma. These interactions were abundant, occurred exclusively between different neurons, and showed substantial structural persistence over several days. Their overall frequency exceeded stochastic predictions across culture densities, and two configurations - proximal and tangential contacts - were selectively enriched above random expectation, whereas soma-crossing contacts were largely consistent with stochastic overlap. DSI composition also changed over development, with proximal contacts becoming progressively more prevalent. At DSI sites, synaptophysin-positive puncta were significantly denser and more intense than on non-interacting dendritic segments, consistent with local enrichment and strengthening of presynaptic specializations. Minimal modeling further indicated that biased formation together with developmental stabilization explains the observed organization better than stochastic geometry alone. These findings identify DSIs a…
How post-mitotic neurons maintain precise transcription factor (TF) levels throughout life remains a fundamental open question. Here, we challenge the prevailing model of positive autoregulation by demonstrating that UNC-3 (Collier/EBF1-4), a dosage-sensitive TF continuously required for cholinergic motor neuron identity in C. elegans, negatively regulates its own expression. Using genetics, biochemistry, and inducible protein depletion, we show this self-repression occurs directly at the transcriptional level and persists beyond development. CRISPR/Cas9 disruption of negative autoregulation causes motor neuron identity and locomotion defects, establishing its functional necessity. Mechanistically, the UNC-3 DNA-binding domain is required and sufficient for self-repression, with an AlphaFold2 screen implicating chromatin factors as interaction partners. Critically, UNC-3 self-repression is continuously counterbalanced by positive input from the HOX cofactor CEH-20/PBX, revealing a dynamic "balancing act" between opposing regulatory inputs that stabilize TF dosage over time. Mutations in the unc-3 ortholog EBF3 cause a neurodevelopmental syndrome, and disease-associated variants disrupt UNC-3 self-repression, revealing a key molecular mechanism underlying the disorder. We propose that negative autoregulation continuously counteracted by positive input represents a broadly applicable principle for maintaining dosage-sensitive TF expression to secure post-mitotic cell identity.
Transcriptomics has transformed our understanding of the brain, but assigning transcriptomic identities to neurons recorded in vivo remains challenging at scale. Existing platforms can pair transcriptomic identity with two-photon calcium imaging in small populations of approximately 100 neurons, but they require recorded cells to be sparse and therefore cannot be applied to large population recordings. Here, we present coppaFISH 3D, a spatially resolved transcriptomics method, and CASTalign, an in silico alignment framework, which together enable transcriptomic identification of thousands of simultaneously recorded cells. coppaFISH 3D detects hundreds of genes in thick 50m fixed sections while preserving tissue integrity, enabling both 3D registration to in vivo imaging and integration with immunofluorescence labelling. The platform is fully powered by open chemistry and open source software, runs on commodity hardware, and can be performed at very low cost per section. It therefore enables transcriptomic identification of recorded neurons at scale, making it possible to study how transcriptomic identity shapes activity in neural populations.
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.
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.
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.
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.
Protein labelling by covalent attachment of a specific substrate to a self-labelling protein tag has become a regular in the life sciences. Herein, we report the design of a two-component labelling system, comprised of a non-fluorescent difluorinated xanthene, called F2X, and a HaloTag mutant engineered for targeted reactivity towards F2X. Upon primary covalent locking of the ligand at the canonical aspartate residue, two proximal lysine residues located at the protein surface can undergo nucleophilic aromatic substitution with the F2X core, building a fluorescent rhodamine via triple-covalent fusion. We used a generalizable in silico pipeline for heuristic conformational sampling of covalent protein-ligand complexes to find suitable mutation sites, culminating in the curation of 7 double-lysine HaloTag mutants for targeted in vitro testing. Reaction with the best-performing mutant, HTPL161K_Q165K, is characterized by full protein mass spectrometry, fluorescence polarization fluorescence lifetime, and fluorescence anisotropy and rationalized by computational modelling. We showcase the system in single molecule microscopy, where obviation of post-labelling purification is a prime advantage when targeting recombinant proteins that may not be expressed in larger quantities, and employ F2X in living cells with reduced photobleaching. Lastly, a cell-impermeable version was obtained by means of sulfonation, exclusively targeting extracellularly exposed HTPKK fused to the neuromodulatory G protein-coupled receptor metabotropic glutamate receptor 2.
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.