Memory of split-belt walking endures weeks in young children and younger adults but less so in older adults Adults and children modify how they move to accommodate persistent changes in their surroundings, called motor adaptation. Walking-related motor adaption can be seen when one walks on a treadmill with two belts running at different speeds, a split-belt treadmill, where a new walking pattern is slowly adopted with practice. This has been suggested as a way to improve left-right symmetry in walking after a stroke. Central to using split-belt walking for rehabilitation is whether the adapted motor pattern is retained over days and weeks, and whether this motor memory is a function of the persons age. When first exposed to split-belt walking, the walking is asymmetric (initial error), resembling a limp. With subsequent exposure, the error is smaller than the initial error, indicating the adaptation was remembered. Here, we explored the persistence of this memory over 24 hours, one week, and two weeks, in young children (3-6 yr old), younger adults (20-30 yr old) and older adults (50-70 yr old). We found that the motor memory declines with the interval duration, but was still evident up to 2 weeks after initial exposure. Retention of the motor memory in children and younger adults was better than older adults. Further, forgetting between trials was seen on the first day of split-belt walking especially in children and older adults, but this forgetting diminished with repeated trials. The results indicate that long-term memory of motor adaptation on the split-belt treadmill is affected by age, but it may be possible to enhance the memory by more frequent and repeated exposure. This suggests that when using split-belt adaptation in rehabilitation, the sessions should ideally be less than one week apart.
Hierachical Resampling for Bagging in Multi-Study Prediction with Applications to Human Neurochemical Sensing We propose the "study strap ensemble," which combines advantages of two common approaches to fitting prediction models when multiple training datasets ("studies") are available: pooling studies and fitting one model versus averaging predictions from multiple models each fit to individual studies. The study strap ensemble fits models to bootstrapped datasets, or "pseudo-studies." These are generated by resampling from multiple studies with a hierarchical resampling scheme that generalizes the randomized cluster bootstrap. The study strap is controlled by a tuning parameter that determines the proportion of observations to draw from each study. When the parameter is set to its lowest value, each pseudo-study is resampled from only a single study. When it is high, the study strap ignores the multi-study structure and generates pseudo-studies by merging the datasets and drawing observations like a standard bootstrap. We empirically show the optimal tuning value often lies in between, and prove that special cases of the study strap draw the merged dataset and the set of original studies as pseudo-studies. We extend the study strap approach with an ensemble weighting scheme that utilizes information in the distribution of the covariates of the test dataset.

Our work is motivated by neuroscience experiments using real-time neurochemical sensing during awake behavior in humans. Current techniques to perform this kind of research require measurements from an electrode placed in the brain during awake neurosurgery and rely on prediction models to estimate neurotransmitter concentrations from the electrical measurements recorded by the electrode. These models are trained by combining multiple datasets that are collected in vitro under heterogeneous conditions in order to promote accuracy of the models when applied to data collected in the brain. A prevailing challenge is deciding how to combine studies or ensemble models trained on different studies to enhance model generalizability.

Our methods produce marked improvements in simulations and in this application. All methods are available in the studyStrap CRAN package.
Microbial populations are shaped by dispersal and recombination in a low biomass subseafloor habitat The subseafloor is a vast habitat that supports microorganisms that have a global scale impact on geochemical cycles. Many of the endemic microbial communities inhabiting the subseafloor consist of small populations under growth-limited conditions. For small populations, stochastic evolutionary events can have large impacts on intraspecific population dynamics and allele frequencies. These conditions are fundamentally different from those experienced by most microorganisms in surface environments, and it is unknown how small population sizes and growth-limiting conditions influence evolution and population structure in the subsurface. Using a two-year, high-resolution environmental time-series, we examine the dynamics of microbial populations from cold, oxic crustal fluids collected from the subseafloor site North Pond, located near the mid-Atlantic ridge. Our results reveal rapid shifts in overall abundance, allele frequency, and strain abundance across the time points observed, with evidence for homologous recombination between coexisting lineages. We show that the subseafloor aquifer is a dynamic habitat that hosts microbial metapopulations that disperse frequently through the crustal fluids, enabling gene flow and recombination between microbial populations. The dynamism and stochasticity of microbial population dynamics in North Pond suggests that these forces are important drivers in the evolution of microbial populations in the vast subseafloor habitat.

Significance StatementThe cold, oxic subseafloor is an understudied habitat that is difficult to access, yet important to global biogeochemical cycles and starkly different compared to microbial habitats on the surface of the Earth. Our understanding of microbial evolution and population dynamics is largely molded by studies of microbes living in surface habitats that can host 10-1,000 times more microbial biomass than is frequently observed in the subsurface. This study provides an opportunity to observe population dynamics within a low biomass, growth-limited environment and reveals that microbial populations in the subseafloor are influenced by changes in selection pressure and gene sweeps. In addition, recombination between strains that have dispersed from elsewhere within the aquifer has an important impact on the evolution of microbial populations. Much of the microbial life on the planet exists under growth-limited conditions and the subseafloor provides a natural laboratory to explore how life evolves in such environments. 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. The compound of baicalein, wogonin, and oroxylin-A inhibiting EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. First detection of herpesvirus and prevalence of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. The role of Kabuki Syndrome genes KMT2D and KDM6A in development: Analysis in Human sequencing data and compared to mice and zebrafish KMT2D and KDM6A are epigenetic regulators that have been implicated in Kabuki Syndrome, a rare congenital birth defect with multiple tissue and organ abnormalities, including craniofacial and heart defects. Our previous study identified human families with mutations in the epigenetic modifiers KMT2D and KDM6A, which is implicated in 32% and 10% of Kabuki Syndrome patients respectively. To understand the connection to Kabuki syndrome patients, and the transcriptional targets of KMT2D and KDM6A in humans, we performed RNA sequencing (seq) of lymphoblastoid cells from Kabuki Syndrome patients carrying mutations in KMT2D and KDM6A. We identified 1995 significant changes in transcriptional targets for KMT2D and 1917 for KDM6A, as compared to control. When compared with RNA-seq datasets obtained from other mouse and zebrafish studies, our analysis revealed KMT2D mutations affect the expression of 76 orthologous genes across all three datasets. Similarliy, KDM6A afftects the expprssion of 7 orthologous genes across three datasets. Despite the differences in cell types, stages, and species in the comparison between the transcriptomic datasets, there are common gene expression changes associated with KMT2D and KDM6A mutations. qPCR on novel zebrafish mutants confirmed the differentially expression in KMT2D or KDM6A mutant backgrounds. Taken together, our results show that KMT2D and KDM6A regulate common and unique genes across humans, mice, and zebrafish for early craniofacial and cardiac development and this information contributes to the understanding of epigenetic dysregulation during development of Kabuki syndrome. Single molecule studies reveal branched pathways for activator-dependent assembly of RNA polymerase II pre-initiation complexes RNA polymerase II (Pol II) transcription reconstituted from purified factors suggests pre-initiation complexes (PICs) can assemble by sequential incorporation of factors at the TATA box. However, these basal transcription reactions are generally independent of activators and co-activators. To study PIC assembly under more realistic conditions, we used single-molecule microscopy to visualize factor dynamics during activator-dependent reactions in nuclear extracts. Surprisingly, Pol II, TFIIF, and TFIIE can pre-assemble on enhancer-bound activators before loading into PICs, and multiple Pol II complexes can bind simultaneously to create a localized cluster. Unlike TFIIF and TFIIE, TFIIH binding is singular and dependent on the basal promoter. Activator-tethered factors exhibit dwell times on the order of seconds. In contrast, PICs can persist on the order of minutes in the absence of nucleotide triphosphates, although TFIIE remains unexpectedly dynamic even after TFIIH incorporation. Our kinetic measurements lead to a new branched model for activator-dependent PIC assembly.

HIGHLIGHTSSingle molecule microscopy reveals unexpected dynamics of RNA Pol II and GTFs

Multiple Pol IIs cluster on UAS/enhancer-bound activators before binding the core promoter

Pol II, TFIIF, and TFIIE, but not TFIIH, can pre-assemble at the UAS/enhancer

Activators increase the rates of Pol II and GTF association with DNA

eTOC BlurbSingle-molecule microscopy experiments by Baek et al. show that RNA polymerase II and basal transcription factors TFIIF and TFIIE preassemble on UAS/enhancer-bound activators, poised for loading into initiation complexes with TFIIH at the core promoter. Transcription activators kinetically enhance factor recruitment, creating a localized cluster of polymerases at the UAS/enhancer. ALLOPURINOL BLOCKS THE AORTIC ANEURYSM IN A MOUSE MODEL OF MARFAN SYNDROME VIA REDUCING AORTIC OXIDATIVE STRESS BackgroundThe pathogenesis and progression of aortic aneurysm in Marfan syndrome (MFS) involves dysregulated TGF-{beta} and nitric oxide signaling, altered hemodynamics, and biomechanical forces. Increasing evidence indicates that redox stress participates in MFS aortopathy, though its contribution is not well established. We reported elevated reactive oxygen species (ROS) formation and NADPH oxidase NOX4 upregulation in MFS patients and mice aortic samples. Here we address the contribution of xanthine oxidoreductase (XOR), which is transcribed as dehydrogenase (XDH) and then post-translationally modified to oxidase (XO), catabolizing mainly purines into uric acid and ROS.

Methods and ResultsWe report that in MFS patients, XOR protein levels increased in aortic samples. In MFS mice (Fbn1C1041G/+), XOR mRNA transcripts augmented in the aorta of young but not older MFS mice. Moreover, the enzymatic activity of XO form increased with respect to XDH. The administration of the XOR inhibitor allopurinol (ALO) blocked the progression of aortic root aneurysm in MFS mice. ALO was also protective when administrated before the appearance of aneurysm. MFS-induced elastic fiber fragmentation, fibrotic remodeling, nuclear translocation of pNRF2, and increased 3-nitrotyrosine levels in the aortic tunica media as well as endothelial dysfunction were all prevented by allopurinol. The large overproduction of H2O2 in MFS aorta did not occur in allopurinol-treated mice whose uric acid plasma levels remained unaltered.

ConclusionsThis study strengthens the concept that redox stress is an important determinant of aortic aneurysm formation and progression in MFS and supports a clinical trial for ALO in the pharmacological treatment of MFS aortopathy.

GRAPHICAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/464182v3_ufig1.gif" ALT="Figure 1">
View larger version (31K):
org.highwire.dtl.DTLVardef@eab02aorg.highwire.dtl.DTLVardef@1d3b39eorg.highwire.dtl.DTLVardef@1b54d0forg.highwire.dtl.DTLVardef@1d61ad0_HPS_FORMAT_FIGEXP  M_FIG C_FIG The renal inflammatory network of nephronophthisis STRUCTURED ABSTRACTO_ST_ABSBACKGROUNDC_ST_ABSThe majority of genetic kidney disease leading to kidney failure is caused by mutations in ciliary genes. How cilia malfunction leads to progressive kidney damage is poorly understood, but recent evidence links ciliopathy genes to CCL2 dependent macrophage recruitment in autosomal dominant polycystic kidney disease (ADPKD), the most studied renal ciliopathy. Whether or not renal inflammation is involved in other renal ciliopathies is unclear.

METHODSWe combined mice models with kidney biopsies and renal epithelial cells sampled from human urine to characterize the renal inflammatory network of nephronophthisis (NPH), the most frequent renal ciliopathy in children.

RESULTSIn human, mutations in cilia genes involved in NPH enhance urine excretion of the chemokine CCL2, causing abnormal macrophage recruitment in kidney tissues from NPH patients. Differing from ADPKD, inactivating Ccl2 specifically in mouse tubular cells does not rescue the NPH phenotype, suggesting that other inflammatory mediators are involved. Using transcriptional data from 2 NPH models, we identify a set of pro-inflammatory cytokines upregulated in this disease, independently of CCL2. The majority of detectable transcripts from this set are specifically upregulated in kidney cells from NPH patients. In line with the function of these cytokines, NPH kidneys show disproportionate neutrophils and T cells infiltrates compared to healthy subject or hypertensive and diabetic chronic kidney disease patients.

CONCLUSIONSThis study reveals that inflammation is a central aspect in human NPH and delineates a specific set of inflammatory mediators that regulates immune cell recruitment in human NPH.

SIGNIFICANCE STATEMENTMutations in genes encoding primary cilia proteins are the leading cause of genetic kidney failure. In autosomal dominant polycystic kidney disease (ADPKD), deregulated cilia signaling leads to kidney infiltration by macrophages through the chemokine CCL2. Little is known about renal inflammation in nephronophthisis (NPH), the most frequent pediatric renal ciliopathy. Using NPH mice models, tissues and cells from NPH patients, we unveil renal inflammation as preeminent feature of NPH. Remarkably, the renal inflammatory evoked by ciliary gene mutations in NPH does not overlap with ADPKD: it is CCL2 independent, involves a prominent recruitment of neutrophils and T cells and a specific cytokine signature. This unforeseen findings strengthen the link between primary cilia and renal inflammation. Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements.

In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification. Remarked Suppression of Aβ42 Protomer-protomer Dissociation Reaction via Pentamer Dimerization Multimeric protein complexes are molecular apparatuses to regulate biological systems and often determine their fate. Among proteins forming such molecular assemblies, amyloid proteins have drawn attention over a half-century since amyloid fibril formation of these proteins is supposed to be a common pathogenic cause for neurodegenerative diseases. This process is triggered by the accumulation of fibril-like aggregates, while the microscopic mechanisms are mostly elusive due to technical limitation of experimental methodologies in individually observing each of diverse aggregate species in the aqueous solution. We then addressed this problem by employing atomistic molecular dynamics simulations for the paradigmatic amyloid protein, amyloid-{beta} (1-42) (A{beta}42). Seven different dimeric forms of oligomeric A{beta}42 fibril-like aggregate in aqueous solution, ranging from tetramer to decamer, were considered. We found additive effects of the size of these fibril-like aggregates on their thermodynamic stability and have clarified kinetic suppression of protomer-protomer dissociation reactions at and beyond the point of pentamer dimer formation. This observation was obtained from the specific combination of the A{beta}42 protomer structure and the physicochemical condition that we here examined, while it is worthwhile to recall that several amyloid fibrils take dimeric forms of their protomers. We could thus conclude that the stable formation of fibril-like protomer dimer should be involved in a turning point where rapid growth of amyloid fibrils is triggered. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. How do stomata evolve on the road to C4 photosynthesis? C4 photosynthesis optimizes plants carbon and water relations, allowing high photosynthetic rate with low stomatal conductance. Stomata have long been believed as a part of C4 syndrome. However, it remains unclear how stomata traits evolved along the path from C3 to C4. Stomatal patterning was examined in Flaveria genus, a model for studying C4 evolution. Comparative, transgenic and semi-in-vitro experiments were used to study molecular basis that underlies stomatal traits along C4 evolution. Novel results: the evolution from C3 to C4 species through intermediate species is accompanied by a stepwise rather than an abrupt change in the stomatal traits. The initial change occurs near Type II and dramatic change occurs at the C4-like species. On the road to C4, stomata become less in number but bigger in size and changes in stomatal density dominates changes in maximum stomatal conductance (gsmax). The reduction of FSTOMAGEN expression underlies altered gsmax between Flaveria species with different photosynthetic pathways and likely occurs in other C4 lineages. Our study provides insight into the pattern, mechanism and role of stomatal evolution along the road towards C4. This work highlights the stomatal traits in the current C4 evolutionary model and the co-evolution of photosynthetic pathway and stomata. A novel 5 prime DNA binding site in RFC facilitates PCNA loading for gap DNA repair RFC uses ATP to assemble PCNA onto primed sites for replicative DNA polymerases {delta} and {gamma}. The RFC pentamer forms a central chamber that binds 3' ss/ds DNA junctions to load PCNA onto DNA during replication. We show here five structures revealing a novel 2nd DNA binding site in RFC that binds a 5' duplex. This 5' DNA site is located in the N-terminal BRCT domain and AAA+ module of the large Rfc1 subunit. It appears 5' DNA binds after 3' DNA binding to RFC. Our structures reveal ideal binding to a 7-nt gap, which includes 2 bp unwound by the clamp loader. Biochemical studies show enhanced binding to 5 and 10 nt gaps, consistent with the structural results. We propose that the 5' site facilitates RFCs PCNA loading activity at a DNA damage-induced gap to recruit gap-filling polymerases. These findings are consistent with genetic studies showing that base excision repair of gaps greater than 1 base requires PCNA and involves the 5' DNA binding domain of Rfc1. We further observe that a 5' end facilitates PCNA loading at an RPA coated 50-nt gap, suggesting a potential role of the RFC 5' DNA site in longer gaps including during lagging strand DNA synthesis. 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. Interactions and information: Exploring task allocation in ant colonies using network analysis In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individuals task - foraging, cleaning or nursing - and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.

HighlightsO_LIWe analysed the interaction networks of six Camponotus fellah colonies
C_LIO_LIWe tested how centrality and information flow were tied to task switching
C_LIO_LINode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups
C_LIO_LIInteractions were correlated with task switching, but the strength of the correlation differed across functional groups
C_LI Full Spectrum Flow Cytometry for High-Dimensional Immunophenotyping of Mouse Innate Lymphoid Cells This 25-parameter, 22-colour full spectrum flow cytometry panel was designed and optimised for the comprehensive enumeration and functional characterisation of innate lymphoid cell (ILC) subsets in mouse tissues (Table 1). The panel presented here allows the discrimination of ILC progenitors (ILCP), ILC1, ILC2, NCR+ ILC3, NCR- ILC3, CCR6+ ILC3 and mature natural killer (NK) cell populations. Further characterisation of ILC and NK cell functional profiles in response to stimulation is provided by the inclusion of subset-specific cytokine markers, and proliferation markers. Development and optimisation of this panel was performed on freshly isolated cells from adult BALB/c lungs and small intestine lamina propria, and ex vivo stimulation with phorbol 12-myrisate 13-acetate, ionomycin, brefeldin A and pro-ILC activating cytokines.

O_TBL View this table:
org.highwire.dtl.DTLVardef@8df9d7org.highwire.dtl.DTLVardef@10dc5d4org.highwire.dtl.DTLVardef@136f44dorg.highwire.dtl.DTLVardef@e10165org.highwire.dtl.DTLVardef@22a0cd_HPS_FORMAT_FIGEXP  M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONSummary Table

C_TABLECAPTION C_TBL Morphology of migration: Associations between wing, and bill morphology and migration in kingbirds (Tyrannus) Morphology is closely linked to locomotion and diet in animals. In animals that undertake long-distance migrations, limb-morphology is under selection to maximize mobility and minimize energy expenditure. Migratory behaviors also interact with diet, such that migratory animals tend to be dietary generalists, while sedentary taxa tend to be dietary specialists. Despite a hypothesized link between migration status and morphology, phylogenetic comparative studies have yielded conflicting findings. We tested for evolutionary associations between migratory status and limb and bill morphology across kingbirds, a pan-American genus of birds with migratory, partially migratory, and sedentary taxa. Migratory kingbirds had longer wings, in agreement with expectations if selection favors improved aerodynamics for long-distance migration. We also found an association between migratory status and bill shape, such that more migratory taxa had wider, deeper, and shorter bills compared to sedentary taxa. However, there was no difference in intraspecific morphological variation among migrants, partial migrants, and residents, suggesting that dietary specialization has evolved independently of migration strategy. The evolutionary links between migration, diet, and morphology in kingbirds uncovered here further strengthen ecomorphological associations that underlie long-distance seasonal movements in animals. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data. Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli (E. coli) and published experimental data. Late-acting self-incompatible system, preferential allogamy and delayed selfing in the heteromorphic invasive populations of Ludwigia grandiflora subsp. hexapetala AO_SCPLOWBSTRACTC_SCPLOWBreeding system influences local population genetic structure, effective size, offspring fitness and functional variation. Determining the respective importance of self- and cross-fertilization in hermaphroditic flowering plants is thus important to understand their ecology and evolution. The worldwide invasive species, Ludwigia grandiflora subsp. hexapetala (Lgh) presents two floral morphs: one self-compatible short-styled morph (S-morph) and one self-incompatible long-styled morph (L-morph). In this study, we identified the breeding systems of western European experimental and natural populations of Lgh by comparing structural characteristics of pollen and style, by studying self- and cross-pollen tube elongations and the viability of the resulting seeds and seedlings in both floral morphs. Our results showed no differences in pollen shape and stigma surfaces no matter the floral morph. In the self-incompatible L-morph flowers, self-pollen tubes were stopped tardily, in the ovarian area, and were unable to fertilize the ovules. This first formal identification of a late-acting, prezygotic self-incompatible system (LSI) in Ludwigia genus contributes a case of LSI in an additional family within the Myrtales order. In the self-compatible S-morph flowers, self-pollen always succeeded to self-fertilize the ovules that nearly all developed into viable seedlings. However, cross-pollen tubes always elongated faster than self-pollen tubes in both morphs. S-morph individuals may thus advantage preferential allogamy over selfing when cross-pollen is available despite its self-compatibility. As expected in late-acting self-incompatible systems, L-morph flowers authorised 0.2{per thousand} of selfed seeds during the uppermost flowering season, that increased to 1{per thousand} at the end of the flowering season. Such delayed selfing resulted in a significant quantity of viable floating seeds. They may contribute to the local regeneration, seed bank and propagation of the L-morph, which may contribute to explain its invasion success worldwide. Management plans of Lgh would gain to consider the breeding systems we identified. Common variants in breast cancer risk loci predispose to distinct tumor subtypes BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction. Deep learning: step forward to high-resolution in vivo shortwave infrared imaging Shortwave infrared window (SWIR: 1000-1700 nm) represents a major improvement compared to the NIR-I region (700-900 nm) in terms of temporal and spatial resolutions in depths down to 4 mm. SWIR is a fast and cheap alternative to more precise methods such as X-ray and opto-acoustic imaging. Main obstacles in SWIR imaging are the noise and scattering from tissues and skin that reduce the precision of the method. We demonstrate that the combination of SWIR in vivo imaging in the NIRIIb region (1500-1700 nm) with advanced deep learning image analysis allows to overcome these obstacles and making a large step forward to high resolution imaging: it allows to precisely segment vessels from tissues and noise, provides morphological structure of the vessels network, with learned pseudo-3D shape, their relative position, dynamic information of blood vascularization in depth in small animals and distinguish the vessels types: artieries and veins. For demonstration we use neural network IterNet that exploits structural redundancy of the blood vessels, which provides a useful analysis tool for raw SWIR images. Spatio-temporal, optogenetic control of gene expression in organoids Organoids derived from stem cells become increasingly important to study human development and to model disease. However, methods are needed to control and study spatio-temporal patterns of gene expression in organoids. To this aim, we combined optogenetics and gene perturbation technologies to activate or knock-down RNA of target genes, at single-cell resolution and in programmable spatio-temporal patterns. To illustrate the usefulness of our approach, we locally activated Sonic Hedgehog (SHH) signaling in an organoid model for human neurodevelopment. High-resolution spatial transcriptomic and single-cell analyses showed that this local induction was sufficient to generate stereotypically patterned organoids in three dimensions and revealed new insights into SHHs contribution to gene regulation in neurodevelopment.

With this study, we propose optogenetic perturbations in combination with spatial transcriptomics as a powerful technology to reprogram and study cell fates and tissue patterning in organoids.