Utility of SARS-CoV-2 infection models using in vitro and in vivo ACE2-lentivirus transduction SARS-CoV-2 uses the human ACE2 (hACE2) receptor for cell attachment and entry, with mouse ACE2 (mACE2) unable to support infection. Herein we describe an ACE2-lentivirus system and illustrate its utility for in vitro and in vivo SARS-CoV-2 infection models. Transduction of non-permissive cell lines with hACE2 imparted replication competence, and transduction with mACE2 containing N30D, N31K, F83Y and H353K substitutions, to match hACE2, rescued SARS-CoV-2 replication. Intranasal hACE2-lentivirus transduction of C57BL/6J mice permitted significant virus replication in lungs. RNA-Seq analyses illustrated that the model involves an acute inflammatory disease followed by resolution and tissue repair, with a transcriptomic profile similar to that seen in COVID-19 patients. Intranasal hACE2-lentivirus transduction of IFNAR-/- and IL-28RA-/- mice lungs was used to illustrate that loss of type I or III interferon responses have no significant effect on virus replication. However, their importance in driving inflammatory responses was illustrated by RNA-Seq analyses. We also demonstrate the utility of the hACE2-lentivirus transduction system for vaccine evaluation in C57BL/6J mice. The ACE2-lentivirus system thus has broad application in SARS-CoV-2 research, providing a tool for both mutagenesis studies and mouse model development.

AUTHOR SUMMARYSARS-CoV-2 uses the human ACE2 (hACE2) receptor to infect cells, but cannot infect mice because the virus cannot bind mouse ACE2 (mACE2). We use an ACE2-lentivirus system in vitro to identify four key amino acids in mACE2 that explain why SARS-CoV-2 cannot infect mice. hACE2-lentivirus was used to express hACE2 in mouse lungs in vivo, with the inflammatory responses after SARS-CoV-2 infection similar to those seen in human COVID-19. Genetically modified mice were used to show that type I and III interferon signaling is required for the inflammatory responses. We also show that the hACE2-lentivirus mouse model can be used to test vaccines. Overall this paper demonstrates that our hACE2-lentivirus system has multiple applications in SARS-CoV-2 and COVID-19 research.
Estimating the rate of plasmid transfer with an adapted Luria-Delbrück fluctuation analysis To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need a reliable estimate of their rate of transfer between bacterial cells. However, accurate estimates of plasmid transfer have remained elusive due to biological and experimental complexity. Current methods to measure transfer rate can be confounded by many factors. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. Inspired by the classic fluctuation analysis of Luria and Delbruck, we develop a novel approach, the Luria-Delbruck method ( LDM), for estimating plasmid transfer rate. Our new approach embraces the stochasticity of conjugation departing from the current deterministic population dynamic methods. In addition, the LDM overcomes obstacles of traditional methods by not being affected by different growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude.

Significance StatementConjugative plasmids play significant roles in the ecology and evolution of microbial communities. Notably, antibiotic resistance genes are often encoded on conjugative plasmids. Thus, conjugation--the transfer of a plasmid copy from one cell to another--is a common way for antibiotic resistance to spread between important clinical pathogens. For both public health modeling and a basic understanding of microbial population biology, accurate estimates of this fundamental rate are of great consequence. We show that widely used methods can lead to biased estimates, deviating from true values by several orders of magnitude. Therefore, we developed a new approach, inspired by the classic fluctuation analysis of Luria and Delbruck, for accurately assessing the rate of plasmid conjugation under a variety of conditions.
Fast ATP-dependent Subunit Rotation in Reconstituted FoF1-ATP Synthase Trapped in Solution FoF1-ATP synthases are ubiquitous membrane-bound, rotary motor enzymes that can catalyze ATP synthesis and hydrolysis. Their enzyme kinetics are controlled by internal subunit rotation, by substrate and product concentrations, by mechanical inhibitory mechanisms, but also by the electrochemical potential of protons across the membrane. Single-molecule Forster resonance energy transfer (smFRET) has been used to detect subunit rotation within FoF1-ATP synthases embedded in freely diffusing liposomes. We now report that kinetic monitoring of functional rotation can be prolonged from milliseconds to seconds by utilizing an Anti-Brownian electrokinetic trap (ABEL trap). These extended observation times allowed us to observe fluctuating rates of functional rotation for individual FoF1-liposomes in solution. Broad distributions of ATP-dependent catalytic rates were revealed. The buildup of an electrochemical potential of protons was confirmed to limit the maximum rate of ATP hydrolysis. In the presence of ionophores or uncouplers, the fastest subunit rotation speeds measured in single reconstituted FoF1-ATP synthases were 180 full rounds per second. This was much faster than measured by biochemical ensemble averaging, but not as fast as the maximum rotational speed reported previously for isolated single F1 complexes uncoupled from the membrane-embedded Fo complex. Further application of ABEL trap measurements should help resolve the mechanistic causes of such fluctuating rates of subunit rotation.

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org.highwire.dtl.DTLVardef@1bd800org.highwire.dtl.DTLVardef@228aeorg.highwire.dtl.DTLVardef@1bce39forg.highwire.dtl.DTLVardef@3f01a_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFigure 1.C_FLOATNO C_FIG IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis through the MAPK Signaling Pathway AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets.

Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway.

ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS.

Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS. Foraging with friends, moving with anyone: effects of the social environment on movement-integrated habitat selection O_LIMovement links the distribution of habitats with the social environment of animals using those habitats; yet integrating movement, habitat selection, and socioecology remains an opportunity for further study.
C_LIO_LIHere, our objective was to disentangle the roles of habitat selection and social association as drivers of collective movement in a gregarious ungulate. To accomplish this objective, we (1) assessed whether socially familiar individuals form discrete social communities and whether social communities have high spatial, but not necessarily temporal, overlap; and (2) we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection analysis.
C_LIO_LIWe used social network analysis to assign individuals to social communities and determine short and long-term social preference among individuals. Using integrated step selection functions (iSSF), we then modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.
C_LIO_LIBased on assignment of individuals to social communities and home range overlap analyses, individuals assorted into discrete social communities, and these communities had high spatial overlap. By unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals foraged with more familiar individuals, but moved collectively with any between foraging patches.
C_LIO_LIOur study demonstrates that social behaviour and space use are inter-related based on spatial overlap of social communities and movement-dependent habitat selection. Movement, habitat selection, and social behaviour are linked in theory. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.
C_LI Towards a cumulative science of vocal markers of autism: a cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children Acoustic atypicalities in speech production are argued to be potential markers of clinical features in Autism Spectrum Disorder (ASD). A recent meta-analysis highlighted shortcomings in the field, in particular small sample sizes and study heterogeneity (Fusaroli et al., 2017). We showcase a cumulative (i.e., explicitly building on previous studies both conceptually and statistically) yet self-correcting (i.e., critically assessing the impact of cumulative statistical techniques) approach to prosody in ASD to overcome these issues.

We relied on the recommendations contained in the meta-analysis to build and analyze a cross-linguistic corpus of multiple speech productions in 77 autistic and 72 neurotypical children and adolescents (>1000 recordings in Danish and US English). We used meta-analytically informed and skeptical priors, with informed priors leading to more generalizable inference. We replicated findings of a minimal cross-linguistically reliable distinctive acoustic profile for ASD (higher pitch and longer pauses) with moderate effect sizes. We identified novel reliable differences between the two groups for normalized amplitude quotient, maxima dispersion quotient, and creakiness. However, the differences were small, and there is likely no one acoustic profile characterizing all autistic individuals. We identified reliable relations of acoustic features with individual differences (age, gender), and clinical features (speech rate and ADOS sub-scores).

Besides cumulatively building our understanding of acoustic atypicalities in ASD, the study shows how to use systematic reviews and meta-analyses to guide the design and analysis of follow-up studies. We indicate future directions: larger and more diverse cross-linguistic datasets, focus on heterogeneity, self-critical cumulative approaches and open science.

Lay SummaryAutistic individuals are reported to speak in distinctive ways. Distinctive vocal production can affect social interactions and social development and could represent a noninvasive way to support the assessment of ASD. We systematically checked whether acoustic atypicalities highlighted in previous articles could be actually found across multiple recordings and two languages. We find a minimal acoustic profile of ASD: higher pitch, longer pauses, increased hoarseness and creakiness of the voice. However, there is much individual variability (by age, sex, language, and clinical characteristics). This suggests that the search for one common "autistic voice" might be naive and more fine-grained approaches are needed. Continental generalization of an AI system for clinical seizure recognition BackgroundElectroencephalogram (EEG) monitoring and objective seizure identification is an essential clinical investigation for some patients with epilepsy. Accurate annotation is done through a time-consuming process by EEG specialists. Computer-assisted systems for seizure detection currently lack extensive clinical utility due to retrospective, patient-specific, and/or irreproducible studies that result in low sensitivity or high false positives in clinical tests. We aim to significantly reduce the time and resources on data annotation by demonstrating a continental generalization of seizure detection that balances sensitivity and specificity.

MethodsThis is a prospective inference test of artificial intelligence on nearly 14,590 hours of adult EEG data from patients with epilepsy between 2011 and 2019 in a hospital in Sydney, Australia. The inference set includes patients with different types and frequencies of seizures across a wide range of ages and EEG recording hours. The artificial intelligence (AI) is a convolutional long short-term memory network that is trained on a USA-based dataset. The Australian set is about 16 times larger than the US training dataset with very long interictal periods (between seizures), which is way more realistic than the training set and makes our false positives highly reliable. We validated our inference model in an AI-assisted mode with a human expert arbiter and a result review panel of expert neurologists and EEG specialists on 66 sessions to demonstrate achievement of the same performance with over an order-of-magnitude reduction in time.

FindingsOur inference on 1,006 EEG recording sessions on the Australian dataset achieved 76.68% with nearly 56 [0, 115] false alarms per 24 hours on average, against legacy ground-truth annotations by human experts, conducted independently over nine years. Our pilot test of 66 sessions with a human arbiter, and reviewed ground truth by a panel of experts, confirmed an identical human performance of 92.19% with an AI-assisted system, while the time requirements reduce significantly from 90 to 7.62 minutes on average.

InterpretationAccurate and objective seizure counting is an important factor in epilepsy. An AI-assisted system can help improve efficiency and accuracy alongside human experts, particularly in low and middle-income countries with limited expert human resources.

FundingsSOAR Fellowship from The University of Sydney, a Microsoft AI for Accessibility grant, and a Research Training Program (RTP) support provided by the Australian Government.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDuring the development of our artificial intelligence (AI) system, we did a systematic review of the scientific literature with search via PubMed for research articles published on seizure detection with the following inclusion criteria: (1) Tests or inference evaluation is conducted on large-scale clinical EEG data; (2) Generalization is attempted or potentials for generalization is considered, e.g., in commercialized tools; (3) Seizure detection delay and real-time (aka. online) operation were not considered critical in this context as long as the test was conducted on raw EEG data. Note that ICU seizure detection or portable seizure alert systems are relying on detection delay and real-time needs. Our keywords include "prospective seizure detection", "automated seizure detection", "non-patient specific seizure detection", "seizure detection on continuous EEG", and "deep learning-based seizure detection" and "machine learning-based seizure detection". We found that the only two categories of works meet our criteria: two research papers published in 2020 and works published by commercial tools developers. We cited a recent review of 89 deep learning-based seizure detection, all of which are retrospective. One work from Stanford reported seizure detection on all ages (pediatric to adult ages) using post-acquisition EEG recordings and provided an avenue for independent evaluation by providing a test on a publicly available Temple University Hospital (TUH) EEG dataset. The other work pivoted on algorithmic-assisted real-time seizure risk monitoring in continuous EEG in neonatal intensive care unit (NICU) with 128 neonates (32 with seizures) showing about 20% improvement in seizure identification over 130 neonates (38 with seizures) with no algorithmic assistance.

Commercial tools we studied are Encevis (EpiScan), Besa, and Persyst. There is a recent comparative study on these tools on 81 patients. Encevis is reported as the best performing tool, and hence we provided a comparative study with Encevis ver. 1.9.2. Encevis is also the only tool that provided an avenue for comparative study on publicly available EEG data. The Stanford work, published in 2020, confirms many false positives with Persyst 13. We excluded our tests on Persyst 14 as it highly under-performed relative to Encevis. Only Stanfords work provides code availability. We compared our results with Stanfords work outcome and provided pilot test results with the Encevis (EpiScan) tool on the Australian dataset, which shows a considerably lower sensitivity.

Added value of this studyTo the best of our knowledge, the current study is the first continental generalization that demonstrates the potential to achieve an expert human-level seizure recognition rate in a clinical setting and in just a fraction of time. The two datasets used in this study are recorded with different infrastructure, which adds to the independence of inference from hardware types and improves clinical utility. This is particularly important as 80% of patients with epilepsy live in low and middle-income countries with limited resources, particularly EEG specialists and neurologists.

Implications of all the available evidenceOur results support the potential benefits of deep learning AI in clinical settings for seizure recognition and its contribution to significant sensitivity over available solutions. Our AI-assisted system achieves more than a ten-fold increase in time efficiency and reports identical performance to human experts for EEG interpretation with access to great neurophysiology support and auxiliary data. Our findings, particularly our tests on an available commercial tool, recommend that the evaluation, test, or inference in AI systems be performed on different datasets, with diverse infrastructures, and on large-scale and realistic sets with long interictal periods. Forecasting the effects of water regulation on the population viability of a threatened amphibian The regulation of river systems alters hydrodynamics and often reduces lateral connectivity between river channels and floodplains. For taxa such as frogs that rely on floodplain wetlands to complete their lifecycle, decreasing inundation frequency can reduce recruitment and increase the probability of local extinction. We virtually reconstructed the inundation patterns of wetlands under natural and regulated flow conditions and built stochastic population models to quantify the probability of local extinction under different inundation scenarios. Specifically, we explored the interplay of habitat size, inundation frequency, and successive dry years on the local extinction probability of the threatened southern bell frog Litoria raniformis in the Murray River floodplains of South Australia. We hypothesised that the changes to wetland inundation resulting from river regulation are a principal driver of L. raniformis declines in this semi-arid system.

Regulation has reduced the inundation frequency of essential habitats below critical thresholds for the persistence of many fresh water-dependent species. Successive dry years raise the probability of local extinction, and these effects are strongest in smaller wetlands. Larger wetlands and those with more frequent average inundation are less susceptible to these effects.

Elucidating these trends informs the prioritisation of treatment sites and the frequency of conservation interventions. Environmental water provision (through pumping or the operation of flow-regulating structures) is a promising tool to reduce the probability of breeding failure and local extinction. Our modelling approach can be used to prioritise the delivery of environmental water to L. raniformis and potentially many other frog species. Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics Data There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

Author summaryReconstruction of multiple association networks from high dimensional omics data is an important topic, especially in biology. Previous studies focused on estimating different networks and detecting common hubs among all classes. Integration of information over different classes of data while allowing difference in the hub nodes is also biologically plausible. Therefore, we propose a method, EDOHA, to jointly construct multiple interaction networks with capacity in finding different hub networks for each class of data. Simulation studies show the better performance over conventional methods. The method has been demonstrated in three real world data. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Superinfection exclusion: a viral strategy with short-term benefits and long-term drawbacks Viral superinfection occurs when multiple viral particles subsequently infect the same host. In nature, several viral species are found to have evolved diverse mechanisms to prevent superinfection (superinfection exclusion) but how this strategic choice impacts the fate of mutations in the viral population remains unclear. Using stochastic simulations, we find that genetic drift is suppressed when superinfection occurs, thus facilitating the fixation of beneficial mutations and the removal of deleterious ones. Interestingly, we also find that the competitive (dis)advantage associated with variations in life history parameters is not necessarily captured by the viral growth rate for either infection strategy. Putting these together, we then show that a mutant with superinfection exclusion will easily overtake a superinfecting population even if the latter has a much higher growth rate. Our findings suggest that while superinfection exclusion can negatively impact the long-term adaptation of a viral population, in the short-term it is ultimately a winning strategy.

Author summaryViral social behaviour has recently been receiving increasing attention in the context of ecological and evolutionary dynamics of viral populations. One fascinating and still relatively poorly understood example is superinfection or co-infection, which occur when multiple viruses infect the same host. Among bacteriophages, a wide range of mechanisms have been discovered that enable phage to prevent superinfection (superinfection exclusion) even at the cost of using precious resources for this purpose. What is the evolutionary impact of this strategic choice and why do so many phages exhibit this behaviour? Here, we conduct an extensive simulation study of a phage population to address this question. In particular, we investigate the fate of viral mutations arising in an environment with a constant supply of bacterial hosts designed to mimic a "turbidostat," as these are increasingly being used in laboratory evolution experiments. Our results show that allowing superinfection in the long-term yields a population which is more capable of adapting to changes in the environment. However, when in direct competition, mutants capable of preventing superinfection experience a very large advantage over their superinfecting counterparts, even if this ability comes at a significant cost to their growth rate. This indicates that while preventing superinfection can negatively impact the long-term prospects of a viral population, in the short-term it is ultimately a winning strategy. SPT6 loss Permits the Transdifferentiation of Keratinocytes into an Intestinal Fate that Recapitulates Barrett's Metaplasia Transient depletion of the transcription elongation factor SPT6 in the keratinocyte has been recently shown to inhibit epidermal differentiation and stratification; instead, they transdifferentiate into a gut-like lineage. We show here that this phenomenon of transdifferentiation recapitulates Barretts metaplasia, the only human pathophysiologic condition in which a stratified squamous epithelium that is injured due to chronic acid reflux is trans-committed into an intestinal fate. The evidence we present here not only lend support to the notion that the keratinocytes are the cell of origin of Barretts metaplasia, but also provide mechanistic insights linking transient acid exposure, downregulation of SPT6, stalled transcription of the master regulator of epidermal fate TP63, loss of epidermal fate and metaplastic progression. Because Barretts metaplasia in the esophagus (BE) is a pre-neoplastic condition with no preclinical human models, these findings have a profound impact on the modeling Barretts metaplasia-in-a-dish.

GRAPHIC ABSTRACT

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org.highwire.dtl.DTLVardef@8ce08aorg.highwire.dtl.DTLVardef@e98c83org.highwire.dtl.DTLVardef@107f521org.highwire.dtl.DTLVardef@16e7523_HPS_FORMAT_FIGEXP  M_FIG C_FIG HIGHLIGHTSO_LIKeratinocytes transdifferentiate into the gut lineage upon depletion of SPT6
C_LIO_LISuch transdifferentiation recapitulates Barretts metaplasia, not the healthy gut
C_LIO_LIAcid downregulates SPT6, which derails the expression and functions of TP63
C_LIO_LISuch downregulation precedes the metaplasia-dysplasia-neoplasia cascade
C_LI Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. Human cells contain myriad excised linear introns with potential functions in gene regulation and as RNA biomarkers By using TGIRT-seq, we identified >8,500 short full-length excised linear intron (FLEXI) RNAs in human cells. Subsets of FLEXIs accumulated in a cell-type specific manner, and [~]200 corresponded to agotrons or mirtrons or encoded snoRNAs. Analysis of CLIP-seq datasets identified potential interactions between FLEXIs and >100 different RNA-binding proteins (RBPs), 53 of which had binding sites in [&ge;]30 different FLEXIs. In addition to proteins that function in RNA splicing, these 53 RBPs included transcription factors, chromatin remodeling proteins, and cellular growth regulators that impacted FLEXI host gene alternative splicing and/or mRNA levels in knockdown datasets. We computationally identified six groups of RBPs whose binding sites were enriched in different subsets of FLEXIs: AGO1-4 and DICER associated with agotrons and mirtrons; AATF, DKC1, NOLCI, and SMNDC1 associated with snoRNA-encoding FLEXIs; two different combinations of alternative splicing factors found in stress granules; and two novel RBP-intron combinations, one including LARP4 and PABC4, which function together in the cytoplasm to regulate ribosomal protein translation. Our results suggest a model in which proteins involved in transcriptional regulation, alternative splicing, or post-splicing secondary functions bind and stabilize cell-type specific subsets of FLEXIs that perform different biological functions and have potential utility as biomarkers. wnt16 exerts pleiotropic effects on bone and lean mass in zebrafish Osteoporosis, a disease of bone fragility, and sarcopenia, a condition of reduced muscle mass and strength, commonly occur in the same individual--a condition termed osteosarcopenia. Genetic variants at the CPED1-WNT16 locus have pleiotropic effects on human bone mineral density (BMD) and lean tissue mass. However, our current understanding of Wnt16 and its influence on bone fails to explain effects on lean mass at this locus. In this study, we sought to better understand the biological mechanism underlying pleiotropy at the CPED1-WNT16 locus on BMD and lean mass. Using single cell analysis, microCT imaging, and genetic approaches in zebrafish, we show that wnt16 exerts dual influence on muscle and bone, and provide evidence that this occurs through a function in somite development, a period in which precursors for both of these tissues are specified. We show that mutations in wnt16 alter vertebral size and lean mass during axial skeletogenesis. We show that wnt16+ cells transcriptionally resemble cells within the amniote dermomyotome, and provide evidence they function as myogenic precursors during embryonic development. We also provide evidence that WNT16 is a gene of major effect on lean mass at the CPED-WNT16 locus. Our studies support the potential for wnt16 to exert pleiotropic effects on bone and lean mass through a function in myogenic precursors. Reconstitution of minimal motility system based on Spiroplasma swimming by expressing two bacterial actins in synthetic minimal bacterium Motility is one of the most important features of life, but its evolutionary origin remains unknown. In this study, we focused on Spiroplasma, commensal, or parasitic bacteria. They swim by switching the helicity of a ribbon-like cytoskeleton that comprises six proteins, each of which evolved from a nucleosidase and bacterial actin called MreB. We expressed these proteins in a synthetic, non-motile minimal bacterium, JCVI-syn3.0B, whose reduced genome was computer-designed and chemically synthesized. The synthetic bacterium exhibited swimming motility with features characteristic of Spiroplasma swimming. Moreover, some combinations of the two proteins produced a helical cell shape and swimming, suggesting that the swimming originated from the differentiation and coupling of bacterial actins, and we also obtained a minimal system for motility of the synthetic bacterium.

One-Sentence SummaryThe minimal system comprised two bacterial actins that provided cell helicity and swimming to the synthetic minimal bacterium. Reconsider phase reconstruction in signals with dynamic periodicity from the modern signal processing perspective Phase is the most fundamental physical quantity when we study an oscillatory time series. There are many tools aiming to estimate phase, most of them are developed based on the analytic function model. Unfortunately, this approach might not be suitable for modern signals with intrinsic nonstartionary structure, including multiple oscillatory components, each with time-varying frequency, amplitude, and non-sinusoidal oscillation, e.g., biomedical signals. Specifically, due to the lack of consensus of model and algorithm, phases estimated from signals simultaneously recorded from different sensors for the same physiological system from the same subject might be different. This fact might challenge reproducibility, communication, and scientific interpretation and thus we need a standardized approach with theoretical support over a unified model. In this paper, after summarizing existing models for phase and discussing the main challenge caused by the above-mentioned intrinsic nonstartionary structure, we introduce the adaptive non-harmonic model (ANHM), provide a definition of phase called fundamental phase, which is a vector-valued function describing the dynamics of all oscillatory components in the signal, and suggest a time-varying bandpass filter (tvBPF) scheme based on time-frequency analysis tools to estimate the fundamental phase. The proposed approach is validated with a simulated database and a real-world database with experts labels, and it is applied to two real-world databases, each of which has biomedical signals recorded from different sensors, to show how to standardize the definition of phase in the real-world experimental environment. Specifically, we report that the phase describing a physiological system, if properly modeled and extracted, is immune to the selected sensor for that system, while other approaches might fail. In conclusion, the proposed approach resolves the above-mentioned scientific challenge. We expect its scientific impact on a broad range of applications. Combined epigenetic and metabolic inhibition blocks platinum-induced ovarian cancer stem cell enrichment High grade serous ovarian cancer (HGSOC) is the most common and aggressive type of ovarian cancer. Platinum resistance is a common occurrence in HGSOC and a main cause of tumor relapse resulting in high patient mortality rates. Recurrent OC is enriched in aldehyde dehydrogenase (ALDH)+ ovarian cancer stem cells (OCSCs), which are resistant to platinum agents. We demonstrated that acute platinum treatment induced a DNA damage-dependent decrease in BRCA1 levels. In a parallel response associated with G2/M arrest, platinum treatment also induced an increase in expression of NAMPT, the rate limiting regulator of NAD+ production from the salvage pathway, and levels of NAD+, the cofactor required for ALDH activity. Concurrent inhibition of DNA methyltransferases (DNMTs) and NAMPT synergistically abrogated the platinum-induced increase in OCSCs. Combining pharmacological inhibitors of DNMT and NAMPT with carboplatin reduced tumorigenesis and OCSC percentage in vivo. We conclude that both epigenetic and metabolic alterations lead to platinum induced OCSC enrichment, providing preclinical evidence that in the neoadjuvant setting, combining DNMT and NAMPT inhibitors with platinum has the potential to reduce OC recurrence and avert the development of platinum resistance. NUCLEAR RETENTION OF LEPTIN/UPD2 REGULATES ORGANISMAL RESILIENCE TO NUTRIENT EXTREMES Adipokines released from the adipocytes function as a systemic adipometer; they impinge on neural circuits to signal nutrient status. On starvation, adipokines must be retained to signal energy deficit; else, it significantly reduces starvation survival. But how fat cells retain adipokines is unclear. Here, we demonstrate that Atg8, a cell-intrinsic autophagy factor, regulates the starvation-induced acute retention of the Leptin Drosophila ortholog Upd2. We show that on starvation, as a direct consequence of Atg8s lipidation, Upd2 accumulates in the nucleus. We illustrate that Upd2s nuclear retention is critical to fat mobilization and increased starvation resilience. Furthermore, nuclear Upd2 promotes the expression of a secreted innate immune gene signature. This hints at an unanticipated connection between adipokine nuclear retention and increased innate immunity. In conclusion, we propose that, during starvation, Atg8s role is not just limited to autophagy but is critical for withholding adipokines in the nucleus to promote starvation resilience.

GRAPHICAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/428913v5_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@1826425org.highwire.dtl.DTLVardef@17cca52org.highwire.dtl.DTLVardef@1c70ac7org.highwire.dtl.DTLVardef@94a024_HPS_FORMAT_FIGEXP  M_FIG C_FIG O_LIIn fed state Upd2 requires Atg8 for nuclear exit and cytosolic localization.
C_LIO_LIAtg8s lipidation on starvation results in Upd2s nuclear accumulation.
C_LIO_LIUpd2 nuclear retention on starvation increases fat mobilization and post-starvation hunger.
C_LIO_LIOn starvation Upd2 nuclear retention increases expression of a secreted innate immune signature.
C_LI Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers BackgroundStress-related neurobehavioral and metabolic disorders are associated with altered circulating adrenal-derived hormones and hyperglycemia. Temporal assessment of glucose and these hormones is critical for insights on an individuals health.

ObjectivesHere we used implantable-telemetry in rats to assess real-time changes in circulating glucose during and after exposure to the air pollutant ozone, and link responses to circulating neuroendocrine stress and metabolic hormones. We also compared rodent glucose and corticosterone (cortisol in humans) responses to humans exposed to ozone.

MethodsFirst, using a cross-over design, we monitored glucose levels during single or repeated ozone exposures (0.0, 0.2, 0.4 and 0.8-ppm) and non-exposure periods in male Wistar-Kyoto-rats implanted with glucose-telemeters. A second cohort of un-implanted rats was exposed to ozone (0.0, 0.4 or 0.8-ppm) for 30-min, 1-hour, 2-hour, or 4-hour with hormones measured immediately after exposure. Then we assessed glucose metabolism in sham and adrenalectomized rats with or without pharmacological interventions of adrenergic and glucocorticoid receptors. Finally, we assessed glucose and cortisol in serum samples from a clinical study involving exposure of human volunteers to air or 0.3 ppm ozone.

ResultsOzone (0.8-ppm) caused hyperglycemia and hypothermia beginning 90-min into exposure, with reversal of effects 4-6 hours post-exposure. Glucose monitoring during four daily 4-hour ozone exposures revealed duration of hyperglycemia, adaptation, and diurnal variations. Ozone-induced hyperglycemia was preceded by increased adrenocorticotropic hormone, corticosterone, and epinephrine, but depletion of thyroid-stimulating, prolactin, and luteinizing hormones. Hyperglycemia was inhibited in rats that were adrenalectomized and/or treated with glucocorticoid inhibitor. The depletion of cortisol was dampened in humans exposed to ozone during intermittent exercise.

DiscussionWe demonstrate for the first time the temporality of neuroendocrine-stress-mediated biological sequalae responsible for ozone-induced metabolic dysfunction as exposure occurs. Real-time glucose monitoring with stress hormones assessment may be useful in identifying interactions among pollutants and stress-related illnesses. Resetting of the 24-nt siRNA landscape in rice zygotes BackgroundThe zygote, a totipotent stem cell, constitutes a critical stage of the life cycle of sexually reproducing organisms. It is produced by the fusion of two differentiated cells -- the egg and sperm, which in plants have radically different siRNA transcriptomes from each other and from multicellular embryos. Due to technical challenges, the epigenetic changes that accompany the zygotic transition are poorly understood.

ResultsHere, we characterized the small RNA transcriptome of rice zygotes. We found widespread redistribution of 24-nt siRNAs relative to gametes, including absence of sperm signature siRNAs, reduction at egg signature siRNA loci, and upregulation at seedling signature siRNA loci. Loci with reduced siRNAs in zygote relative to egg were gene-distal and heterochromatic, while loci with increased siRNAs relative to egg had a similar genomic distribution to canonical siRNA loci. Although both egg and zygote siRNA loci had higher mCHH level in wildtype than in drm2 embryo, zygote but not egg siRNA loci were associated with hypermethylation in mature embryo. A small fraction of siRNA loci (~1%) called siren loci accounted for 60% of all siRNAs within zygote siRNA loci, that likely arose from maternal carryover as they had similarly abundant siRNAs in egg; these siren loci were not associated with embryo hypermethylation.

ConclusionsTaken together, our results indicate re-distribution of siRNAs in rice zygotes towards the canonical vegetative profile, that are consistent with the initiation of resetting of the gametic epigenome before the first embryonic division. TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. SUMM4 biochemically complex couples insulator function and DNA replication timingcontrol The mechanisms that establish DNA replication timing programs in eukaryotes remain incompletely understood. Drosophila SNF2-related factor SUUR imparts under-replication (UR) of late-replicating intercalary heterochromatin (IH) in polytene chromosomes. We developed a proteomics technique termed MERCI to isolate a native complex SUMM4 comprising SUUR and chromatin boundary protein Mod(Mdg4)-67.2. Mod(Mdg4) stimulates the ATPase activity of SUUR and is required for its normal spatiotemporal distribution in vivo. Both SUMM4 subunits mediate the activities of gypsy insulator disrupting enhancer-promoter interactions and establishing chromatin barriers. Furthermore, SuUR or mod(mdg4) mutations reverse UR of IH. Our findings uncover a critical role for architectural proteins in attenuating replication fork progression and suggest an alternative mechanism for DNA replication timing that does not depend on an asynchronous firing of replication origins.

One-Sentence SummaryA stable protein complex comprising an insulator factor and a SNF2-like ATPase imparts late replication of heterochromatin. ZAF -- The First Open Source Fully Automated Feeder for Aquatic Facilities In the past few decades, aquatic animals have become popular model organisms in biology, spurring a growing need for establishing aquatic facilities. Zebrafish are widely studied and relatively easy to culture using commercial systems. However, a challenging aspect of maintaining aquatic facilities is animal feeding, which is both time- and resource-consuming. We have developed an open-source fully automatic daily feeding system, Zebrafish Automatic Feeder (ZAF). ZAF is reliable, provides a standardized amount of food to every tank, is cost-efficient and easy to build. The advanced version, ZAF+, allows for the precise control of food distribution as a function of fish density per tank, and has a user-friendly interface. Both ZAF and ZAF+ are adaptable to any laboratory environment and facilitate the implementation of aquatic colonies. Here we provide all blueprints and instructions for building the mechanics, electronics, fluidics, as well as to setup the control software and its user-friendly graphical interface. Importantly, the design is modular and can be scaled to meet different user needs. Furthermore, our results show that ZAF and ZAF+ do not adversely affect zebrafish culture, enabling fully automatic feeding for any aquatic facility.