Biology subjects

Schwartz, E.

Publications and source records attributed to Schwartz, E..

16 recordsLinked to original sources

bioRxiv2026

Quantitative stable isotope probing to measure in situ growth of protist populations

Soil protists shape microbial food webs and nutrient cycling, yet methods for measuring their population growth in soil have lagged behind the taxonomic resolution available from 18S rRNA gene sequencing. Microscopy-based approaches can estimate abundance and growth, but with limited taxonomic resolution. Here, we tested whether quantitative stable isotope probing (qSIP) can provide reproducible, sequencing-resolved growth measurements for soil protists. We incubated soil with natural-abundance or {superscript 1} O-labeled water and measured taxon-specific 18O enrichment in DNA using three common 18S rRNA gene primer sets. 18O enrichment values were positively correlated across datasets, with relationships closest to 1:1 after poorly resolved taxonomic assignments were excluded, indicating that qSIP provides reproducible population-level growth signals across marker choices. We then compared 18S amplicon profiles from unfractionated DNA with qSIP-derived growth measurements across a soil moisture gradient. Amplicon profiles showed small shifts in relative abundances of major protist groups, whereas qSIP revealed a large moisture response in the growing community: 7 ASVs were growing at 20% field capacity compared with 143 at 80% field capacity, representing 1.6% and 63.3% of total protist relative abundance, respectively. Average growth was <1% day{square}1 in the two driest treatments, increasing to 2.1% day{square}1 at 60% and 5.6% day{square}1 at 80% field capacity; among growing taxa, rates averaged 8.7% and 8.3% day{square}1 in the two wetter treatments. By pairing taxonomic resolution with isotope-based growth estimates, qSIP with 18O-H2O moves soil protist ecology toward quantitative population dynamics: identifying which taxa grow, how fast, and how growth responds to the environment.

microbiology↗

bioRxiv2026

Face-selective responses correlate with deep networks that learn from environment feedback

AO_SCPLOWBSTRACTC_SCPLOWDeep neural networks have shown high accuracy in modeling neural responses in the visual system, but most models rely on supervised learning, which requires training on ground-truth labels that are typically unavailable in real-world settings. While unsupervised models can address this limitation, they miss another key aspect: visual representations are shaped by feedback from the environment. We introduce a reinforcement learning (RL) model of face perception that incorporates both input stimuli and feedback from the environment. Inspired by human interactions, we train the model to approach faces yielding positive interactions and avoid faces yielding negative interactions. Using intracortical electroencephalography (iEEG) data and Representational Dissimilarity Matrices (RDMs), we evaluate the models ability to account for neural responses. Our RL model performs at the same level as supervised and unsupervised models, capturing neural responses to complex visual stimuli. The findings suggest that RL models are a promising approach for understanding perception. Significance StatementUnderstanding how the brain encodes faces is central to vision science. Existing models rely on supervised learning, which requires ground-truth labels that are often unavailable in real-world settings, or on unsupervised learning, which ignores the role of environmental-feedback in shaping visual representations. We introduce a reinforcement learning (RL) model that learns through environmental feedback, simulating human interactions by associating approaching faces with positive interactions and avoiding faces with negative interactions. Using intracortical electroencephalography (iEEG) data from face-selective regions, we show that an RL model with a variational DenseNet encoder accounts for neural representations comparably to supervised and unsupervised models. Task and architecture jointly shaped representational geometry, highlighting the importance of both learning objective and encoder design. These findings suggest the potential of RL-based approaches to understand neural representations of naturalistic faces.

neuroscience↗

bioRxiv2026

Rapid Changes in Transcription During a Feast-Famine Event

AbstractSoil microbes have sophisticated mechanisms to detect and respond to short pulses of C inputs, often involving changes in gene-expression. We studied gene transcription in a soil microbial community before, and 8, 24, and 48h after glucose addition (0.7 mg C g-1 dry soil) to understand how microbes react to periods of substrate excess and subsequent starvation. The relative transcript abundance of genes associated with energy metabolism and biosynthesis of amino acids, lipids, nucleotides, and cell wall components increased 8h after glucose addition. By 24 and 48h, the abundances of these transcripts reversed. Transcript abundance for genes associated with degradation of lipids, nucleotides, and (hetero)cyclic hydrocarbons decreased at 8h, but increased 24 and 48h after glucose addition. Simultaneously with a rise in transcripts for energy production and biosynthesis at 8h, transcription of regulatory genes for the exponential growth phase and ribosome assembly and maturation increased. In contrast, at 24 and 48h, transcript abundance for genes associated with ribosomal hibernation, sporulation, and regulation of the stationary phase increased, while transcripts for regulators for the exponential phase, and ribosome activation decreased. Based on changes in transcript abundance of phosphoenolpyruvate carboxylase and pyruvate carboxylase, it appeared that 8h after glucose addition glycolytic activity was high, however, gluconeogenesis returned at 24 and 48h. High levels of transcripts for nrtC-ntrB indicated N limitation 8 and 24h after glucose addition. Transcripts associated with Type VI Secretion Systems increased 24 and 48h after start of the experiment, suggesting a short lag between primary consumers and predatory bacteria. These results illustrate how metatranscriptome analysis can be used to study the ecophysiology of soil microbes providing details on the timing of exponential and stationary phase processes, coordination between anabolism and catabolism, and emerging nutrient limitations in natural soil communities. Research HighlightsO_LIWe studied gene transcription of a soil microbial community after glucose addition C_LIO_LITranscript abundances for biosynthesis and energy production initially increased, while those for degradation decreased C_LIO_LITranscripts of regulators and sporulation genes indicated start of stationary phase at 24h C_LIO_LINitrogen limitation induced transcription of nitrogen stress genes C_LI

ecology↗

bioRxiv2025

Hierarchical and Spatial Mapping of Whole-Brain c-Fos Activity Reveals Distinct Opioid and Withdrawal Neuronal Ensembles

How opioid exposure and withdrawal states shape brain activity at the systems and circuit level remains poorly understood. Here, we use whole-brain, cellular-resolution c-Fos mapping to define brain-wide activity patterns and neuronal ensembles associated with morphine administration and withdrawal. To account for the brains anatomically nested structure, we developed and applied a hierarchical statistical framework that detects region-specific changes in activity and outperforms conventional methods that treat brain regions as individual, unrelated units. These distributed signals formed ensembles with consistent and anatomically structured patterns of activity, both within subregions and across multiple connected brain areas. By combining TRAP2-based activity tagging with acute whole-brain c-Fos staining, we identified morphine- and withdrawal-activated ensembles and found that they are largely non-overlapping at the single-cell level, even within the same brain region. Integration with existing spatial transcriptomics datasets identified molecular markers for these state-specific ensembles in key brain areas such as the nucleus of accumbens, amygdala and ventral tegmental areas. Lastly, by integrating Allen mouse whole-brain transcriptional datasets, we identified the molecular identity of the morphine- administration and withdrawal ensembles. These findings define dissociable neuronal ensembles that encode opposing drug states and introduce a scalable framework for linking whole-brain activity to molecular and circuit-level mechanisms. HighlightsO_LIWhole-brain neural activity mapping identifies the regional and spatial difference of morphine-administration and withdrawal neuronal ensembles. C_LIO_LIBRANCH, a hierarchical statistical testing framework, offers increased sensitivity and anatomical interpretability for whole-brain datasets. C_LIO_LITRAP2-based activity tagging reveals brain-wide separation of acute morphine and withdrawal ensembles at the cellular level. C_LIO_LIA systematic analysis of the whole brain neural activity data combined with spatial transcriptomic data revealed molecular features of opioid-related neural ensembles. C_LI

neuroscience↗

bioRxiv2025

Internal DNA standards for Isopycnic Centrifugation of Environmental DNA in Quantitative Stable Isotope Probing

Element assimilation rates or the DNA replication rate of microbial taxa can be measured in environmental samples through quantitative DNA-stable isotope probing (DNA-qSIP). Here, we introduce a set of DNA standards that may be used to quantify the density of DNA extracted from environmental samples after isopycnic centrifugation. The standards are approximately 9 Kbp PCR products with either isotopically enriched (98 atom% 15N, 13C) nucleotides or natural abundance nucleotides and have densities that differ by 0.051 g/mL. The internal standards were tested in a DNA-qSIP analysis of bacterial populations in soil exposed to 63 atom% H218O, performed in two different laboratories with different equipment and protocols. While fractionation results, including number of fractions taken and differences in density between adjacent fractions, between the two laboratories were different, the internal standards allowed the two data sets to be compared, and both research groups found similar Excess Atom Fraction (EAF) of oxygen-18 in the DNA of bacterial taxa. These internal DNA standards allow direct comparison of DNA-qSIP results from different experiments regardless of operator, tracer enrichment levels, protocol or equipment used and can support the creation of a large global database that contains qSIP results from many different laboratories. ImportanceDNA-qSIP is an important technique in microbial ecology that allows the growth and nutrient assimilation rates of microbial taxa, including those that have not yet been cultured, to be measured. Growth and assimilation rates are extremely variable parameters in microbial ecology because most of the microbial community is dormant and inactive, which complicates linking microbial populations to ecosystem processes. DNA-qSIP is increasingly practiced in a range of laboratories, using different equipment, isotopes, substrates, and protocols, making comparison of results among different research groups challenging. Here we describe the development of internal standards, 2 pieces of DNA with different isotopic content and hence buoyant density, that can be added to environmental DNA before isopycnic centrifugation. Our results show the internal DNA standards allow DNA-qSIP results to be compared across laboratories and could contribute to the formation of a large DNA-qSIP database that contains growth or nutrient assimilation rates of microbial taxa from many different experiments.

microbiology↗

bioRxiv2025

Composition, growth, succession, and function in the Cladophora microbiome: insights from quantitative Stable Isotope Probing and NanoSIMS imaging

The branching green macroalga Cladophora glomerata and its epiphytic microbiome dominate summer biomass in the Eel River, a Northern California river under Mediterranean (summer drought, winter rain) seasonality. Green Cladophora streamers proliferate in early summer, then change to yellow and then red-brown as epiphyte loads increase. We characterized successional changes in epiphytic bacteria on Cladophora, examining both community composition and growth rates, using quantitative Stable Isotope Probing (qSIP) and16S rRNA gene amplicon sequencing. The number of bacterial taxa increased with succession while growth rates peaked in the middle stage. NanoSIMS imaging confirmed high sulfur (S) concentrations in Cladophora cell walls relative to surrounding biomass, coinciding with a bloom of sulfur bacteria (bacteria that reduce or oxidize sulfur/sulfates). In general, relative abundances and growth rates were independent, indicating that either metric alone is insufficient for understanding how taxonomy and functional groups affect ecosystem processes. For instance, the relative abundance of nitrogen fixers peaked in the late summer when their relative growth rates were slowest. Such patterns may be driven by space competition limiting growth. Together, changes in abundance and relative growth rates suggest different limiting factors for different functional groups in the Cladophora microbiome at multiple successional stages.

microbiology↗

bioRxiv2024

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

cancer biology↗

bioRxiv2023

SKP2 knockout in Rb1/p53 deficient mouse models of osteosarcoma induces immune infiltration and drives a transcriptional program with a favorable prognosis

PurposeOsteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. One putative proto-oncogene in OS is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase. We previously demonstrated that SKP2 knockout in murine OS improved survival and delayed tumorigenesis. Here we aim to define the SKP2 drives transcriptional program and its clinical implication in OS. Experimental DesignWe performed RNA-sequencing (RNA-seq) on tumors from a transgenic OS mouse model with conditional Trp53 and Rb1 knockouts in the osteoblast lineage ("DKO": Osx1-Cre;Rb1lox/lox;p53lox/lox) and a triple-knockout model with additional Skp2 germline knockout ("TKO": Osx1-Cre;Rb1lox/lox;p53lox/lox;SKP2-/-). We validated our RNA-seq findings using qPCR and immunohistochemistry. To investigate the clinical implications of our results, we analyzed a human OS patient cohort ("NCI-TARGET OS") with RNA-seq and clinical data. ResultsWe found large differences in gene expression after SKP2 knockout. Strikingly, we observed increased expression of genes related to immune microenvironment infiltration in TKO tumors. We observed significant increases in signature genes for macrophages and to a lesser extent, T cells, B cells and vascular cells. We also uncovered a set of relevant transcription factors that may mediate the changes. In OS patient cohorts, high expression of genes upregulated in TKO was correlated with favorable overall survival, which was largely explained by the macrophage gene signatures. This relationship was further supported by our finding that SKP2 expression was negatively correlated with macrophage infiltration in the NCI-TARGET OS and the TCGA Sarcoma cohort. ConclusionOur findings indicate that SKP2 may mediate immune exclusion from the OS tumor microenvironment, suggesting that SKP2 modulation in OS may induce anti-tumor immune activation. Translational RelevanceOsteosarcoma (OS) is an aggressive bone malignancy. Standard care treatment involving chemotherapy and surgery remains unchanged for decades. OS prognosis remains poor and targeted therapies are critically needed. Immunotherapy failed in clinical trials despite extensive genomic instability, suggesting OS tumors employ active immune exclusion. One putative oncogene in OS is SKP2, which activates cell proliferation. SKP2 is correlated with worse prognosis in patients and knockout of SKP2 improved survival in murine OS. Here, we performed comparative transcriptomic analysis between transgenic OS murine models with SKP2 knockout and controls. We showed that SKP2 knockout dramatic increased immune gene expression largely due to macrophage, and to a lesser extent lymphocytes, infiltration. Interestingly, we found that the increased gene program uncovered from our SKP2 knockout model was correlated with improved survival in OS patients. Our findings indicate a completely new function for SKP2 in mediating immune exclusion in sarcoma and suggest that SKP2 inhibition may lead to improved immune activation and potential treatment.

cancer biology↗

bioRxiv2021

Edaphic controls on genome size and GC content of bacteria in soil microbial communities

Bacteria in soil microbial communities are crucial to terrestrial ecosystem function, yet our understanding of the fundamental characteristics of their genomes, such as GC content and genome size, is not complete. Much of our understanding of the mechanisms which shape their genomic traits is derived from other systems or from isolated bacteria. Here we determined average genome size, GC content, codon usage, and amino acid content from 398 soil metagenomes across a broad geographic range and used machine-learning to determine which environmental parameters most strongly explain the distribution of these traits. We found that genomic trait averages were most related to pH, which we suggest is primarily due to the correlation of pH with several environmental parameters, especially soil carbon content. Low pH soils had higher carbon to nitrogen ratios (C:N) and tended to have communities with lower GC content and larger genomes, potentially a response to increased physiological stress and a requirement for metabolic diversity. Conversely, smaller genomes with high GC content were associated with high pH and low soil C:N, indicating potential resource driven selection against AT base pairs. As soil bacteria tend to be more carbon limited, smaller genomes with higher GC content may reduce the cost of reproduction in carbon-limited soils. Similarly, we found that nutrient conservation also applied to amino acid stoichiometry, where bacteria in soils with low C:N ratios tended to code for amino acids with lower C:N. Together, these relationships point towards fundamental mechanisms that underpin nucleotide and amino acid selection in soil bacterial communities.

ecology↗

bioRxiv2021

Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment

The human brain varies across individuals in its morphology, function, and cognitive capacities. Variability is particularly high in phylogenetically modern regions associated with higher order cognitive abilities, but its relationship to the layout and strength of functional networks is poorly understood. In this study we disentangled the variability of two key aspects of functional connectivity: strength and topography. We then compared the genetic and environmental influences on these two features. Genetic contribution is heterogeneously distributed across the cortex and differs for strength and topography. In heteromodal areas genes predominantly affect the topography of networks, while their connectivity strength is shaped primarily by random environmental influence such as learning. We identified peak areas of genetic control of topography overlapping with parts of the processing stream from primary areas to network hubs in the default mode network, suggesting the coordination of spatial configurations across those processing pathways. These findings provide a detailed map of the diverse contribution of heritability and individual experience to the strength and topography of functional brain architecture.

neuroscience↗

bioRxiv2021

Soil, ocean, hot spring, and host-associated environments reveal unique selection pressures on genomic features of bacteria in microbial communities

Free-living bacteria in nutrient limited environments often exhibit small genomes which curb the cost of reproduction - a phenomenon known as genomic streamlining. Streamlining has been associated with a suite of traits such as reduced GC content, fewer 16S rRNA copies, and a lower abundance of regulatory genes, such as sigma ({sigma}) factors. Here, we analyzed these traits from 116 publicly available metagenomes derived from marine, soil, host associated, and thermophilic communities. In marine and thermophilic communities, genome size and GC content declined in parallel, but GC content was higher in thermophilic communities. In soils, the relationship between genome size and GC content was negative, suggesting a different selection pressure on genome size and GC content in soil bacteria. The abundance of {sigma}-factors varied with average genome size, ecosystem type, and the specific functions regulated by the sigma factor. In marine environments, housekeeping and heat-shock {sigma}-factor genes (rpoD and rpoH respectively) increased as genome size declined, and {sigma}-factor responsible for flagella biosynthesis (fliA) decreased, suggesting a trade-off between nutrient conservation and chemotaxis. In soils, a high abundance of fliA and the stress response {sigma}-factor gene (rpoS) was associated with smaller average genome size and often located in harsh and/or carbon-limited environments such as deserts or agricultural fields - suggesting an increased capacity for stress response and mobility in nutrient-poor soils. This work showcases how ecosystem-specific environmental constraints force trade-offs which are then embedded in the genomic features of bacteria in microbial communities, specifically genome size, GC content, and regulatory genes, and further highlights the importance of considering these features in microbial community analysis.

microbiology↗

bioRxiv2021

Rapid response of nitrogen cycling gene transcription to labile carbon amendments in a soil microbial community

Episodic inputs of labile carbon (C) to soil can rapidly stimulate nitrogen (N) immobilization by soil microorganisms. However, the transcriptional patterns that underlie this process remain unclear. In order to better understand the regulation of N cycling in soil microbial communities, we conducted a 48 h laboratory incubation with an agricultural soil where we stimulated the uptake of inorganic N by amending the soil with glucose. We analyzed the metagenome and metatranscriptome of the microbial communities at four timepoints that corresponded with changes in N availability. The relative abundances of genes remained largely unchanged throughout the incubation. In contrast, glucose addition rapidly increased transcription of genes encoding for ammonium and nitrate transporters, enzymes responsible for N assimilation into biomass, and genes associated with the N regulatory network. This upregulation coincided with an increase in transcripts associated with glucose breakdown and oxoglutarate production, demonstrating a connection between C and N metabolism. When concentrations of ammonium were low, we observed a transient upregulation of genes associated with the nitrogen fixing enzyme nitrogenase. Transcripts for nitrification and denitrification were downregulated throughout the incubation, suggesting that dissimilatory transformations of N may be suppressed in response to labile C inputs in these soils. These results demonstrate that soil microbial communities can respond rapidly to changes in C availability by drastically altering the transcription of N cycling genes. IMPORTANCEA large portion of activity in soil microbial communities occurs in short time frames in response to an increase in C availability, affecting the biogeochemical cycling of nitrogen. These changes are of particular importance as nitrogen represents both a limiting nutrient for terrestrial plants as well as a potential pollutant. However, we lack a full understanding of the short-term effects of labile carbon inputs on the metabolism of microbes living in soil. Here, we found that soil microbial communities responded to labile carbon addition by rapidly transcribing genes encoding proteins and enzymes responsible for inorganic nitrogen acquisition, including nitrogen fixation. This work demonstrates that soil microbial communities respond within hours to carbon inputs through altered gene expression. These insights are essential for improved understanding of the microbial processes governing soil organic matter production, decomposition, and nutrient cycling in natural and agricultural ecosystems.

microbiology↗

bioRxiv2021

The Functional Significance of Bacterial Predators

Predation structures food webs, influences energy flow, and alters rates and pathways of nutrient cycling through ecosystems, effects that are well documented for macroscopic predators. In the microbial world, predatory bacteria are common, yet little is known about their rates of growth and roles in energy flows through microbial food webs, in part because these are difficult to quantify. Here, we show that growth and carbon uptake were higher in predatory bacteria compared to non-predatory bacteria, a finding across 15 sites, synthesizing 82 experiments and over 100,000 taxon-specific measurements of element flow into newly synthesized bacterial DNA. Obligate predatory bacteria grew 36% faster and assimilated carbon at rates 211% higher than non-predatory bacteria. These differences were less pronounced for facultative predators (6% higher growth rates, 17% higher carbon assimilation rates), though high growth and carbon assimilation rates were observed for some facultative predators, such as members of the genera Lysobacter and Cytophaga, both capable of gliding motility and wolfpack hunting behavior. Added carbon substrates disproportionately stimulated growth of obligate predators, with responses 63% higher than non-predators for the Bdellovibrionales and 81% higher for the Vampirovibrionales, whereas responses of facultative predators to substrate addition were no different from non-predators. This finding supports ecological theory that higher productivity increases predator control of lower trophic levels. These findings also indicate that the functional significance of bacterial predators increases with energy flow, and that predatory bacteria influence element flow through microbial food webs.

ecology↗

bioRxiv2020

Characterization of a new Leishmania major isolate for use in a controlled human infection model

Leishmaniasis is widely regarded as a vaccine-preventable disease, but the costs required to reach pivotal Phase 3 studies and uncertainty about which candidate vaccines should be progressed into human studies significantly limits progress in vaccine development for this neglected tropical disease. Controlled human infection models (CHIM) provide a pathway for accelerating vaccine development and to more fully understand disease pathogenesis and correlates of protection. Here, we describe the isolation, characterization and GMP manufacture of a new clinical isolate of Leishmania major. Two fresh isolates of L. major from Israel were initially compared by genome sequencing, in vivo infectivity and drug sensitivity in mice, and development and transmission competence in sand flies, allowing one (L. major_MRC-02) to be selected for GMP production. This study addresses a major roadblock in the development of vaccines for leishmaniasis, providing a key resource for CHIM studies of sand fly transmitted cutaneous leishmaniasis.

microbiology↗

bioRxiv2020

Measurement error and resolution in quantitative stable isotope probing: implications for experimental design

Quantitative stable isotope probing (qSIP) estimates the degree of incorporation of an isotope tracer into nucleic acids of metabolically active organisms and can be applied to microorganisms growing in complex communities, such as the microbiomes of soil or water. As such, qSIP has the potential to link microbial biodiversity and biogeochemistry. As with any technique involving quantitative estimation, qSIP involves measurement error; a more complete understanding of error, precision and statistical power will aid in the design of qSIP experiments and interpretation of qSIP data. We used several existing qSIP datasets of microbial communities found in soil and water to evaluate how variance in the estimate of isotope incorporation depends on organism abundance and on the resolution of the density fractionation scheme. We also assessed statistical power for replicated qSIP studies, and sensitivity and specificity for unreplicated designs. We found that variance declines as taxon abundance increases. Increasing the number of density fractions reduces variance, although the benefit of added fractions declines as the number of fractions increases. Specifically, nine fractions appear to be a reasonable tradeoff between cost and precision for most qSIP applications. Increasing replication improves power and reduces the minimum detectable threshold for inferring isotope uptake to 5 atom%. Finally, we provide evidence for the importance of internal standards to calibrate the %GC to mean weighted density regression per sample. These results should benefit those designing future SIP experiments, and provide a reference for metagenomic SIP applications where financial and computational limitations constrain experimental scope. ImportanceOne of the biggest challenges in microbial ecology is correlating the identity of microorganisms with the roles they fulfill in natural environmental systems. Studies of microbes in pure culture reveal much about genomic content and potential functions, but may not reflect an organisms activity within its natural community. Culture-independent studies supply a community-wide view of composition and function in the context of community interactions, but fail to link the two. Quantitative stable isotope probing (qSIP) is a method that can link the identity and function of specific microbes within a naturally occurring community. Here we explore how the resolution of density-gradient fractionation affects the error and precision of qSIP results, how they may be improved via additional replication, and cost-benefit balanced scenarios for SIP experimental design.

microbiology↗

bioRxiv2019

Cross-species Functional Alignment Reveals Evolutionary Hierarchy Within the Connectome

Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we demonstrate a function-based method for cross-species cortical alignment that leverages recent advances in understanding cortical organization and that enables the quantification of homologous regions across species, even when their location is decoupled from anatomical landmarks. Critically, our method establishes that cross-species similarity in cortical organization decreases with geodesic distance from unimodal systems, and culminates in the most pronounced changes in posterior regions of the default network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default network, as the apex of a cognitive hierarchy, as is seen in humans, is a relatively recent evolutionary adaptation. They also highlight functional changes in regions such as the posterior cingulate cortex and angular gyrus as key influences on uniquely human features of cognition.

neuroscience↗