Biology subjects

Johnston, A.

Publications and source records attributed to Johnston, A..

At least 19 recordsLinked to original sources

bioRxiv2026

High Intensity Interval Training in Aged Female Mice Preserves Physical, Cognitive, and Cardiovascular Function

BACKGROUNDAlong with advancing age comes declines in physical, cognitive, and cardiovascular function. This diminished capacity may lead to decreased ability to perform activities of daily living, disability onset, and loss of independence. Exercise is a regenerative medicine therapy that can mitigate this loss of function. High intensity interval training (HIIT) is an aerobic exercise paradigm consisting of intense activity periods interspersed with bouts of active recovery. Previously we demonstrated that HIIT preserved physical function in adult, middle-aged, and older male mice. However, whether HIIT preserves physical, cognitive, and cardiovascular function, mitigates frailty, and improves brain and heart health in older adult female mice remains unknown. HYPOTHESISCognitive, physical, and cardiovascular function in older adult female C57BL/6 will be preserved in exercised mice (HIIT) versus sedentary control (SED). METHODSMice (HIIT and SED, both n=9, 24m at end) were tested pre/post-intervention for physical (rotarod, treadmill, grip meter, inverted cling, voluntary wheel running, activity monitor), cognitive (open field, novel object recognition, puzzle box, y-maze), and cardiovascular (blood pressure, echocardiogram) function, body composition, and whole body calorimetry. The mice underwent 14-weeks of HIIT training with progressive volume and intensity. RESULTSHIIT significantly (p<0.05) increased or preserved function in many tests including: aerobic capacity (+71% HIIT versus, vs, no change, NC, in SED), four limb strength/endurance (-67% SED vs -28% HIIT), forelimb strength (-16% SED vs NC HIIT), overall motor function (NC SED vs +39% HIIT), executive function (NC SED vs +73% HIIT), and exploratory behavior, which improved across multiple tests with HIIT while remaining unchanged in SED. HIIT also reduced both systolic blood pressure by 12% (-17 mmHg) and mean arterial pressure by -16 mmHg. In addition, HIIT significantly reduced cardiac fibrosis, increased muscle fiber type 2a percentage, reduced IL-1{beta} expression in the hypothalamus, and mitigated frailty onset. CONCLUSIONHIIT significantly reduced age-related functional loss in all three domains assessed while preventing frailty onset in older adult females and improving markers of brain and heart health.

physiology↗

bioRxiv2026

Dual-acting Estrogen Receptor Modulator-Histone Lysine Demethylase Inhibitors

Epigenetic dysfunction and the malfunction of endocrine proteins such as estrogen receptor alpha (ER) are two key mechanisms for the sustenance of breast carcinoma. Agents that target ER signaling malfunctions are standard therapies for ER-dependent breast cancer (BCa) subtypes. Small molecule inhibitors of epigenetic modifiers, histone lysine demethylases (KDMs), have shown promise as therapeutic agents for several BCa subtypes. We demonstrated herein that the integration of ER antagonist (Tamoxifen) and agonist (17-ethinylestradiol) ligands with deferiprone (DFP)-derived KDM inhibitor moiety furnished dual-acting agents Tam-KDMi and EED-KDMi, respectively. These agents showed robust on-target effects and potent BCa cells-selective anti-proliferative activities. The Tam-KDMi are cytotoxic to both ER(+) and ER(-) BCa cells, while the lack of ER-signaling inhibition conferred an enhanced ER(-) cells cytotoxic to the EED-KDMi. Representative lead compounds Tam-KDMi DW-116 and EED-KDMi DW-088 and DW-95 significantly reduce tumor growth in murine xenograft models of ER(-) and ER(+) BCas with TGI as high as 70%. Collectively, our data showed that DW-116, DW-088 and DW-95 have a high potential as leads for the development of new agents for the treatment of BCa subtypes regardless of the tumor ER expression status.

cancer biology↗

bioRxiv2026

Ongoing lymphoid HIV production drives pyroptosis and GLP-1 counter-regulation in ART-suppressed infection

Despite effective antiretroviral therapy (ART), many people with HIV (PWH) exhibit persistent immune activation (IA) and suffer metabolic comorbidities. We investigated whether residual HIV production in lymphoid tissues drives IA. Among 20 ART-suppressed PWH, HIV RNA+ cells were detected in lymph nodes and correlated directly with markers of pyroptosis, assessed via cleaved gasdermin D positivity, but not with most plasma cytokines or IA markers. Notably, glucagon-like peptide 1 (GLP-1), an enteroendocrine hormone with anti-inflammatory roles, was upregulated in the ileum of PWH and correlated directly with systemic cytokines but inversely with lymph node pyroptosis. These findings suggest that chronic occult inflammation in people with successfully suppressed HIV infection is mediated by persistent virus production in lymph nodes leading to pyroptosis, which may trigger compensatory anti-inflammatory enteroendocrine activation that may dampen pyroptosis. Targeting pyroptosis or enhancing GLP-1 signaling represent potential therapeutic strategies for modulating IA and managing metabolic comorbidities in PWH. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/698696v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@af8909org.highwire.dtl.DTLVardef@4dbc95org.highwire.dtl.DTLVardef@197ff48org.highwire.dtl.DTLVardef@1f9051a_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Transcriptomic Signature and PROTAC Strategy Revealed Histone Lysine Demethylase as a Target of Anticancer Activity of Deferiprone.

Deferiprone (DFP) is an iron chelator approved for treating iron overload in thalassemia patients. Recent observations have suggested that DFP has promising anticancer activities ascribed to several mechanisms including reduction of the intracellular free labile iron and zinc ion pools and inhibition of the activities of other intracellular targets, including ribonucleotide reductase (RNR). We previously reported that DFP inhibits the demethylase activities of several Fe(II)/- ketoglutarate dependent histone lysine demethylases (KDMs) at much lower concentrations at which it inhibits RNR activities and/or reduces the labile intracellular iron and zinc ion pools. In this study, we used RNA sequencing (RNA seq) and PROTACs strategies to validate and quantify the contribution of intracellular KDM inhibition to the antiproliferative activities of DFP. We report herein that DFP elicited gene expression signature that is largely similar to that of JIB-04, an established KDM inhibitor (KDMi), in two breast cancer (BCa) cells (MCF-7 and MDA-MD-231). Importantly, RNA seq revealed that DFP and JIB-04 downregulated the expression of hypoxia-inducible factor 1 (HIF-1), an oncogene whose expression is commonly modulated through histone demethylation mediated by KDMs and degraded by several KDMi. Moreover, DFP-derived PROTACs elicited enhanced cancer cell selective antiproliferative activities and intracellular on-target effects, downregulating several KDMs implicated in the etiology of BCa cells, including a strong degradation of KDMs 2A, 3A and 5B, and a moderate degradation of KDMs 4A-C, 5C, 6B. Collectively, our data supports KDM inhibition as a key mechanism of anticancer activity of DFP and identifies PROTAC is a viable strategy to obtain novel DFP analogs with improved potency and therapeutic index.

cancer biology↗

bioRxiv2025

Identification of a novel CLPX variant in a mixed breed dog with anemia and spinocerebellar ataxia

Spinocerebellar ataxia (SCA) or hereditary ataxia is a progressive neurodegenerative disorder primarily manifesting as cerebellar or spinocerebellar dysfunction, resulting in the loss of motor control and voluntary muscle coordination. SCAs are typically inherited conditions, with causative genetic variants identified in multiple genes in people and across various dog breeds. Recently, an atypical case of SCA was documented in a mixed breed dog. In addition to the classic clinical signs and spinocerebellar lesions of SCA, the dog had retinal and optic nerve degeneration and severe, non-regenerative anemia. Whole-genome sequence (WGS) of the affected dog did not reveal any previously identified canine SCA-associated variants. Subsequent variant filtering against a control cohort of over 700 unaffected dog genomes identified a homozygous 4-base-pair frameshift deletion in caseinolytic mitochondrial matrix peptidase chaperone subunit X (CLPX) [XM_038580726.1:c.1723_1726del]. CLPX encodes a subunit of the ATP-dependent ClpXP protease, a molecular chaperone involved in mitochondrial protein degradation. The variant is predicted to cause a frameshift and a premature stop codon within 17 amino acids, truncating approximately 6.64% of the protein. Our study is the first to explore the association of CLPX variants with SCA in any species. Given the high evolutionary conservation of CLPX, this report of a CLPX variant associated with SCA in a dog may have relevance for understanding CLPX-related neurodegeneration and/or anemia in other species. Author SummaryA young mixed-breed dog developed a gait abnormality that progressively worsened, together with vision loss, and severe anemia. Despite treatment, the dogs condition deteriorated, and he was humanely euthanized. An autopsy revealed extensive abnormalities in the brain, spinal cord, eyes, and bone marrow. These histologic findings supported a diagnosis of spinocerebellar ataxia (SCA), also known as hereditary ataxia, which is a genetic neurological disorder that results in impaired movement and diminished coordination. Genetic analysis identified a previously unreported mutation in the CLPX gene. CLPX plays a key role in mitochondrial protein quality control by helping break down damaged or misfolded proteins within mitochondria--cell structures critical for energy production that are particularly crucial in high-demand tissues like the brain. This mutation likely disrupted normal CLPX protein function, leading to both nerve damage and impaired blood cell production. While related genes are known to cause similar conditions in humans, this is the first time a naturally occurring CLPX variant has been identified in an SCA case in any species. Because CLPX is highly conserved between dogs and humans, this finding may offer valuable insights into rare inherited neurological diseases in people.

genomics↗

bioRxiv2024

A 3D in vitro assay to study combined immune cell infiltration and cytotoxicity

Immune cell-mediated killing of cancer cells in a solid tumor is prefaced by a multi-step infiltration cascade of invasion, directed migration, and cytotoxic activities. In particular, immune cells must invade and migrate through a series of different extracellular matrix (ECM) boundaries and domains before reaching and killing their target tumor cells. These infiltration events are a central challenge to the clinical success of CAR T cells against solid tumors. The current standard in vitro cell killing assays measure cell cytotoxicity in an obstacle-free, two-dimensional (2D) microenvironment, which precludes the study of 3D immune cell-ECM interactions. Here, we present a 3D combined infiltration/cytotoxicity assay based on an oil-in-water microtechnology. This assay measures stromal invasion following extravasation, migration through the stromal matrix, and invasion of the solid tumor in addition to cell killing. We compare this 3D cytotoxicity assay to the benchmark 2D assay through tumor assembloid cocultures with immune cells and engineered immune cells. This assay is amenable to an array of imaging techniques, which allows direct observation and quantification of each stage of infiltration in different immune and oncological contexts. We establish the 3D infiltration/cytotoxicity assay as an important tool for the mechanistic study of immune cell interactions with the tumor microenvironment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/586980v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@6a161dorg.highwire.dtl.DTLVardef@d1e5d3org.highwire.dtl.DTLVardef@47b87corg.highwire.dtl.DTLVardef@a0e051_HPS_FORMAT_FIGEXP M_FIG The 3D combined infiltration/cytotoxicity assay captures three important steps of immune cell infiltration into the solid tumor microenvironment: (1) circulating immune cells extravasate and invade the stromal matrix, (2) immune cells migrate through the stromal matrix to reach the tumor core, and (3) immune cells that successfully navigate the stroma must cross a basement membrane boundary secreted by the cancer cells to contact and kill the cancer cells within a solid tumor. C_FIG

cancer biology↗

bioRxiv2024

A Novel Liver Cancer-Selective Histone Deacetylase Inhibitor Is Effective Against Hepatocellular Carcinoma and Induces Durable Responses with Immunotherapy

Hepatocellular cancer (HCC) progression is facilitated by gene-silencing chromatin histone hypoacetylation due to histone deacetylases (HDACs) activation. However, inhibiting HDACs -- an effective treatment for lymphomas -- has shown limited success in solid tumors. We report the discovery of a class of HDAC inhibitors (HDACi) that demonstrates exquisite selective cytotoxicity against human HCC cells. The lead compound STR-V-53 (3) showed a favorable safety profile in mice and robustly suppressed tumor growth in orthotopic xenograft models of HCC. When combined with the anti-HCC drug sorafenib, STR-V-53 showed greater in vivo efficacy. Moreover, STR-V-53 combined with anti-PD1 therapy increased the CD8+ to regulatory T-cell (Treg) ratio and survival in an orthotopic HCC model in immunocompetent mice. This combination therapy resulted in durable responses in 40% of the mice. Transcriptomic analysis revealed that STR-V-53 primed HCC cells to immunotherapy through HDAC inhibition, impaired glucose-regulated transcription, impaired DNA synthesis, upregulated apoptosis, and stimulated the immune response pathway. Collectively, our data demonstrate that the novel HDACi STR-V-53 is an effective anti-HCC agent that can induce profound responses when combined with standard immunotherapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/587062v2_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@28281corg.highwire.dtl.DTLVardef@617aa9org.highwire.dtl.DTLVardef@1bc198dorg.highwire.dtl.DTLVardef@31852e_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Indicators of a data-deficient taxa: combining bird and environmental data enhances predictive accuracy of wild bee richness

Widespread declines in wild bee populations necessitate urgent action, but there remains insufficient data to guide conservation efforts. Addressing this data deficit, we investigated the relative performance of environmental and/or taxon-based indicators to predict wild bee richness in the eastern and central U.S. Our methodology leveraged publicly available data on bees (SCAN and GBIF data repository), birds (eBird participatory science project) and land cover data (USGS Cropland Data Layer). We used a Bayesian variable selection algorithm to select variables that best predicted bee richness using two datasets: a semi-structured dataset covering a wide geographical and temporal range and a structured dataset covering a focused extent with a standardized protocol. We demonstrate that an indicator based on the combination of bird and land cover data was better at predicting wild bee richness across broad geographies than indicators based on land cover or birds alone, particularly for the semi-structured dataset. In the case of wild bees specifically, we suggest that bird and land cover data serve as useful indicators to guide monitoring and conservation priorities until the quality and quantity of bee data improve.

ecology↗

bioRxiv2023

Advancing bee conservation in the US: gaps and opportunities in data collection and reporting

Bee conservation in the U.S. is currently hindered by challenges associated with assessing the status and trends of a diverse group of >3000 species, many of which are rare, endemic to small areas, and/or exhibit high inter-annual variation in population size. Fundamental information about the distribution of most species across space and time, thus, is lacking yet urgently needed to assess population status, guide conservation plans, and prioritize actions among species and geographies. Using wild bee data from two public data repositories representing the contiguous U.S., we evaluated the availability and sufficiency of data for use in species assessments of wild bees. We also examined the number of bee species recorded in each U.S. state and the proportion of species with recent records (2012-2021). Although efforts to monitor bees continue to grow, there remains a massive paucity of data. Exceedingly few records (0.04%) reported both sampling protocol and effort, greatly limiting the usefulness of the data. Few species or locations have adequate publicly available data to support analyses of population status or trends, and fewer than half of species have sufficient data to delineate geographic range. Despite an exponential increase in data submissions since the 2000s, only 47% of species were reported within the last decade, which may be driven by how data are collected, reported, and shared, or may reflect troubling patterns of local or large-scale declines and extirpations. Based on our analysis, we provide recommendations to improve the quality and quantity of data that can be used to detect, understand, and respond to changes in wild bee populations.

ecology↗

bioRxiv2023

A robust measure of metacognitive sensitivity and confidence criteria

Humans experience feelings of confidence in their decisions. In perception, these feelings are typically accurate - we tend to feel more confident about correct decisions. The degree of insight people have into the accuracy of their decisions is known as metacognitive sensitivity. Currently popular methods of estimating metacognitive sensitivity are subject to interpretive ambiguities because they assume that humans experience normally-shaped distributions of different experiences when they are repeatedly exposed to a single input. If, however, people have skewed distributions of experiences, or distributions with excess kurtosis (i.e. a distribution containing greater numbers of extreme experiences than is predicted by a normal distribution), calculations can erroneously underestimate metacognitive sensitivity. Here, we describe a means of estimating metacognitive sensitivity that is more robust against violations of the normality assumption. This improved method relies on estimating the precision with which people transition between making categorical decisions with relatively low to high confidence, and on comparing this with the precision with which they transition between making different types of perceptual category decision. The new method can easily be added to standard behavioral experiments. We provide free Matlab code to help researchers implement these analyses and procedures in their own experiments. Public Significance StatementSignal-detection theory is one of the most popular frameworks for analysing data from experiments of human behaviour - including investigations of confidence. The authors demonstrate that if a key assumption of this framework is inadvertently violated, analyses of confidence can lead to unwarranted conclusions. They develop a new and more robust measure of confidence.

neuroscience↗

bioRxiv2023

Measuring the perception and metacognition of time

The ability of humans to identify and reproduce short time intervals (in the region of a second) may be affected by many factors ranging from the gender of the individual observer, through the attentional state, to the precise spatiotemporal structure of the stimulus. The relative roles of these very different factors are a challenge to describe and define; several methodological approaches have been used to achieve this to varying degrees of success. Here we describe a new paradigm affording not only a first-order measurement of the perceived duration of an interval but also a second-order metacognitive judgement of perceived time. This approach, we argue, expands the form of the data generally collected in duration-judgements and allows more detailed comparison of psychophysical behaviour to the underlying theory. We also describe a measurement model which provides estimates of the variability of the temporal estimates and the metacognitive judgments allowing comparison to an ideal observer. We fit the model to data collected for judgements of 750ms (bisecting 1500ms) and 1500ms (bisecting 3000ms) intervals across three stimulus modalities (Visual, Audio & Audiovisual). This enhanced form of data on a given interval judgement and the ability to track its progression on a trial-by-trial basis offers a way of looking at the different roles that subject-based, task-based and stimulus-based factors have on the perception of time.

neuroscience↗

bioRxiv2022

On why we lack confidence in signal-detection-based analyses of confidence

Signal-detection theory (SDT) is one of the most popular frameworks for analyzing data from studies of human behavior - including investigations of confidence. SDT-based analyses of confidence deliver both standard estimates of sensitivity (d), and a second estimate based only on high-confidence decisions - meta d. The extent to which meta d estimates fall short of d estimates is regarded as a measure of metacognitive inefficiency, quantifying the contamination of confidence by additional noise. These analyses rely on a key but questionable assumption - that repeated exposures to an input will evoke a normally-shaped distribution of perceptual experiences (the normality assumption). Here we show, via analyses inspired by an experiment and modelling, that when distributions of experiences do not conform with the normality assumption, meta d can be systematically underestimated relative to d. Our data therefore highlight that SDT-based analyses of confidence do not provide a ground truth measure of human metacognitive inefficiency. Public Significance StatementSignal-detection theory is one of the most popular frameworks for analysing data from experiments of human behaviour - including investigations of confidence. The authors show that the results of these analyses cannot be regarded as ground truth. If a key assumption of the framework is inadvertently violated, analyses can encourage conceptually flawed conclusions.

neuroscience↗

bioRxiv2022

Profiling emergent behaviors from single-cell motility

Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, we introduce CaMI, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a large dataset (n=74,253 cells). This framework allows quantification of spatial and temporal heterogeneities, determination of single-cell motility behaviors across various biological conditions, and provides a visualization scheme for direct interpretation of dynamic cell behaviors. Importantly, CaMI reveals insights that conventional cell motility analyses may overlook, showcasing its utility in uncovering robust biological insights. Together, we present a multivariate framework to classify emergent patterns of single-cell motility, emphasizing the critical role of cellular heterogeneity in shaping cell behaviors across populations. TeaserA computational framework to identify and classify single-cell motility patterns and phenotypic heterogeneity across biological conditions.

bioengineering↗

bioRxiv2022

Root System Architecture and Environmental Flux Analysis in Mature Crops using 3D Root Mesocosms

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of full-sized plant root systems in 3-dimensions, we developed customized mesocosm growth containers. While highly scalable, the design presented here uses an internal volume of 45 ft3 (1.27 m3), suitable for large crop and bioenergy grass root systems to grow largely unconstrained. Furthermore, they allow for the excavation and preservation of 3-dimensional RSA, and facilitate the collection of time-resolved subterranean environmental data. Sensor arrays monitoring matric potential, temperature and CO2 levels are buried in a grid formation at various depths to assess environmental fluxes at regular intervals. Methods of 3D data visualization of fluxes were developed to allow for comparison with root system architectural traits. Following harvest, the recovered root system can be digitally reconstructed in 3D through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. We developed a pipeline to extract features from the 3D point clouds, or from derived skeletons that include point cloud voxel number as a proxy for biomass, total root system length, volume, depth, convex hull volume and solidity as a function of depth. Ground-truthing these features with biomass measurements from manually dissected root systems showed a high correlation. We evaluated switchgrass, maize, and sorghum root systems to highlight the capability for species wide comparisons. We focused on two switchgrass ecotypes, upland (VS16) and lowland (WBC3), in identical environments to demonstrate widely different root system architectures that may be indicative of core differences in their rhizoeconomic foraging strategies. Finally, we imposed a strong physiological water stress and manipulated the growth medium to demonstrate whole root system plasticity in response to environmental stimuli. Hence, these new "3D Root Mesocosms" and accompanying computational analysis provides a new paradigm for study of mature crop systems and the environmental fluxes that shape them.

plant biology↗

bioRxiv2021

Identifying cell-to-cell variability in internalisation using flow cytometry

Biological heterogeneity is a primary contributor to the variation observed in experiments that probe dynamical processes, such as internalisation. Given that internalisation is a critical process by which many therapeutics and viruses reach their intracellular site of action, quantifying cell-to-cell variability in internalisation is of high biological interest. Yet, it is common for studies of internalisation to neglect cell-to-cell variability. We develop a simple mathematical model of internalisation that captures the dynamical behaviour, cell-to-cell variation, and extrinsic noise introduced by flow cytometry. We calibrate our model through a novel distribution-matching approximate Bayesian computation algorithm to flow cytometry data of internalisation of anti-transferrin receptor antibody in a human B-cell lymphoblastoid cell line. Our model reproduces experimental observations, identifies cell-to-cell variability in the internalisation and recycling rates, and, importantly, provides information relating to inferential uncertainty. Given that our approach is agnostic to sample size and signal-to-noise ratio, our modelling framework is broadly applicable to identify biological variability in single-cell data from internalisation assays and similar experiments that probe cellular dynamical processes.

cell biology↗

bioRxiv2021

Mismatch between bird species sensitivity and the protection of intact habitats across the Americas

Protected areas, the most prevalent international policy mechanism for biodiversity conservation, are highly heterogeneous in their effectiveness at buffering ecosystems and species habitats from human pressure. Protected areas with intense human pressure cannot protect species that are highly sensitive to human activities. Here, we use 60 million bird observations from the eBird citizen science platform to estimate the sensitivity to human pressure of each bird species breeding in the Americas (Nearctic and Neotropical regions). We find that high-sensitivity species, while found in all ecoregions, are concentrated in the tropical biomes. Ecoregions with large proportions of high-sensitivity species do not have more intact protected habitat, resulting in a low coverage of intact protected habitat for many high-sensitivity species. What is more, 139 high-sensitivity species have little or no intact protected habitat within their distributions while being threatened with extinction. Finally, we show that protected area intactness is decreasing faster in ecoregions with many high-sensitivity species. Our results highlight a major mismatch between species conservation needs and the coverage of intact protected habitats, and will likely hamper the long-term effectiveness of protected areas at retaining species. We highlight ecoregions where the protection and management of intact habitats, complemented by the restoration of degraded ones, is urgently needed to avoid extinctions.

ecology↗

bioRxiv2021

Ribovore: ribosomal RNA sequence analysis for GenBank submissions and database curation

BackgroundThe DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron. ResultsTo improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. Nine freely available blastn rRNA databases created and maintained with Ribovore are used for checking incoming GenBank submissions and used by the blastn browser interface at NCBI. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8,350 taxa. ConclusionRibovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.

bioinformatics↗

bioRxiv2020

Are alpha-band oscillations a default dynamic of the human visual brain, or a product of ongoing visual processes?

One of the seminal findings of cognitive neuroscience is that the power of alpha-band ([~]10 Hz) brain waves, in occipital regions, increases when people close their eyes. This has encouraged the view that alpha oscillations are a default dynamic, to which the visual brain returns in the absence of input. Accordingly, we might be unable to increase the power of alpha oscillations when the eyes are closed, above the level that would usually ensue. Here we report counter evidence. We used electroencephalography (EEG) to record brain activity when people had their eyes open and closed, before and after they had adapted to radial motion. The increase in the power of alpha oscillations when people closed their eyes was enhanced by adaptation to a broad range of radial motion speeds. This effect was greatest for 10Hz motion, but robust for other frequencies, and specifically for 7.5Hz. This last observation is important, as it rules against an ongoing entrainment of activity, at the adaptation frequency, as an explanation for our results. Instead, our data show that visual processes remain active when people close their eyes, and these can be modulated by adaptation to increase the power of alpha oscillations in occipital brain regions.

neuroscience↗