Regulation of blood-brain barrier integrity by microbiome-associated methylamines and cognition by trimethylamine N-oxide BackgroundCommunication between the gut microbiota and the brain is primarily mediated via soluble microbe-derived metabolites, but the details of this pathway remain poorly defined. Methylamines produced by microbial metabolism of dietary choline and L-carnitine have received attention due to their proposed association with vascular disease, but their effects upon the cerebrovascular circulation have hitherto not been studied.

ResultsHere we use an integrated in vitro/in vivo approach to show that physiologically relevant concentrations of the dietary methylamine trimethylamine N-oxide (TMAO) enhanced blood-brain barrier (BBB) integrity and protected it from inflammatory insult, acting through the tight junction regulator annexin A1. In contrast, the TMAO precursor trimethylamine (TMA) impaired BBB function and disrupted tight junction integrity. Moreover, we show that long-term exposure to TMAO protects murine cognitive function from inflammatory challenge, acting to limit astrocyte and microglial reactivity in a brain region-specific manner.

ConclusionOur findings demonstrate the mechanisms through which microbiome-associated methylamines directly interact with the mammalian BBB, with consequences for cerebrovascular and cognitive function.
Protein degradation sets the fraction of active ribosomes at vanishing growth Growing cells adopt common basic strategies to achieve optimal resource allocation under limited resource availability. Our current understanding of such "growth laws" neglects degradation, assuming that it occurs slowly compared to the cell cycle duration. Here we argue that this assumption cannot hold at slow growth, leading to important consequences. We propose a simple framework showing that at slow growth protein degradation is balanced by a fraction of "maintenance" ribosomes. Consequently, active ribosomes do not drop to zero at vanishing growth, but as growth rate diminishes, an increasing fraction of active ribosomes performs maintenance. Through a detailed analysis of compiled data, we show that the predictions of this model agree with data from E. coli and S. cerevisiae. Intriguingly, we also find that protein degradation increases at slow growth, which we interpret as a consequence of active waste management and/or recycling. Our results highlight protein turnover as an underrated factor for our understanding of growth laws across kingdoms.

Author summaryThe idea that simple quantitative relationships relate cell physiology to cellular composition dates back to the 1950s, but the recent years saw a leap in our understanding of such "growth laws", with relevant implications regarding the interdependence between growth, metabolism and biochemical networks. However, recent works on nutrient-limited growth mainly focused on laboratory conditions that are favourable to growth. Thus, our current mathematical understanding of the growth laws neglects protein degradation, under the argument that it occurs slowly compared to the timescale of the cell cycle. Instead, at slow growth the timescales of mass loss from protein degradation and dilution become comparable. In this work, we propose that protein degradation shapes the quantitative relationships between ribosome allocation and growth rate, and determines a fraction of ribosomes that do not contribute to growth and need to remain active to balance degradation.
Natural selection promotes the evolution of recombination 1: between the products of natural selection Shuffling ones genetic material with another individual seems a risky endeavor more likely to decrease than to increase offspring fitness. This intuitive argument is commonly employed to explain why the ubiquity of sex and recombination in nature is enigmatic. It is predicated on the notion that natural selection assembles selectively well-matched combinations of genes that recombination would break up resulting in low-fitness offspring - a notion often stated in the literature as a self-evident premise. We show however that, upon closer examination, this premise is flawed: we find to the contrary that natural selection in fact has an encompassing tendency to assemble selectively mismatched gene combinations; recombination breaks up these selectively mismatched combinations (on average), assembles selectively matched combinations, and should thus be favored. The new perspective our findings offer suggests that sex and recombination are not so enigmatic but are instead unavoidable byproducts of natural selection. 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. Microtubule inhibitors identified through non-biased screening enhance DNA transfection efficiency by delaying p62-dependent ubiquitin recruitment Ectopic gene expression is an indispensable tool in biology and medicine, but is often limited by the low efficiency of DNA transfection. We previously reported that depletion of the autophagy receptor p62/SQSTM1 enhances DNA transfection efficiency by preventing the degradation of transfected DNA. Therefore, p62 is a potential target for drugs to increase transfection efficiency. To identify such drugs, a non-biased high-throughput screening was applied to over 4,000 compounds from the Osaka University compound library, and their p62-dependency was evaluated. The top-scoring drugs were mostly microtubule inhibitors, such as colchicine and vinblastine, and all of them showed positive effects only in the presence of p62. To understand the p62-dependent mechanisms, the time required for p62-dependent ubiquitination, which is required for autophagosome formation, was examined using polystyrene beads that were introduced into cells as materials that mimicked transfected DNA. Microtubule inhibitors caused a delay in ubiquitination. Furthermore, the level of phosphorylated p62 at S405 was markedly decreased in the drug-treated cells. These results suggest that microtubule inhibitors inhibit p62-dependent autophagosome formation. Our findings demonstrate for the first time that microtubule inhibitors suppress p62 activation as a mechanism for increasing DNA transfection efficiency and provide solutions to increase efficiency. Predicting gene regulatory networks from multi-omics to link genetic risk variants and neuroimmunology to Alzheimers disease phenotypes BackgroundGenome-wide association studies have found many genetic risk variants associated with Alzheimers disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. To address these problems, we performed an integrative multi-omics analysis of genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.

MethodFirst, given the population gene expression data of a cohort, we construct and cluster its gene co-expression network to identify gene co-expression modules for various AD phenotypes. Next, we predict transcription factors (TFs) regulating co-expressed genes and AD risk SNPs that interrupt TF binding sites on regulatory elements. Finally, we construct a gene regulatory network (GRN) linking SNPs, interrupted TFs, and regulatory elements to target genes and gene modules for each phenotype in the cohort. This network thus provides systematic insights into gene regulatory mechanisms from risk variants to AD phenotypes.

ResultsOur analysis predicted GRNs in three major AD-relevant regions: Hippocampus, Dorsolateral Prefrontal Cortex (DLPFC), Lateral Temporal Lobe (LTL). Comparative analyses revealed cross-region-conserved and region-specific GRNs, in which many immunological genes are present. For instance, SNPs rs13404184 and rs61068452 disrupt SPI1 binding and regulation of AD gene INPP5D in the Hippocampus and LTL. However, SNP rs117863556 interrupts bindings of REST to regulate GAB2 in DLPFC only. Driven by emerging neuroinflammation in AD, we used Covid-19 as a proxy to identify possible regulatory mechanisms for neuroimmunology in AD. To this end, we looked at the GRN subnetworks relating to genes from shared AD-Covid pathways. From those subnetworks, our machine learning analysis prioritized the AD-Covid genes for predicting Covid-19 severity. Decision Curve Analysis also validated our AD-Covid genes outperform known Covid-19 genes for classifying severe Covid-19 patients. This suggests AD-Covid genes along with linked SNPs can be potential novel biomarkers for neuroimmunology in AD. Finally, our results are open-source available as a comprehensive functional genomic map for AD, providing a deeper mechanistic understanding of the interplay among multi-omics, brain regions, gene functions like neuroimmunology, and phenotypes. The Consequences of Differential Origin Licensing Dynamics in Distinct Chromatin Environments MCM complexes are loaded onto chromosomes to license DNA replication origins in G1 phase of the cell cycle, but it is not yet known how mammalian MCM complexes are adequately distributed to both euchromatin and heterochromatin. To address this question, we combined time-lapse live-cell imaging with fixed cell immunofluorescence imaging of single human cells to quantify the relative rates of MCM loading in heterochromatin and euchromatin at different times within G1. We report here that MCM loading in euchromatin is faster than in heterochromatin in very early G1, but surprisingly, heterochromatin loading accelerates relative to euchromatin loading in middle and late G1. These different loading dynamics require ORCA-dependent differences in ORC distribution during G1. A consequence of heterochromatin origin licensing dynamics is that cells experiencing a truncated G1 phase from premature cyclin E expression enter S phase with under-licensed heterochromatin, and DNA damage accumulates preferentially in heterochromatin in the subsequent S/G2 phase. Thus G1 length is critical for sufficient MCM loading, particularly in heterochromatin, to ensure complete genome duplication and to maintain genome stability. Polycystins are upregulated in fibrotic kidneys and promote renal fibrosis Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. Source-sink connectivity: A novel interictal EEG marker for seizure localization Over 15 million epilepsy patients worldwide have drug-resistant epilepsy (DRE). Successful surgery is a standard of care treatment for DRE but can only be achieved through complete resection or disconnection of the epileptogenic zone (EZ), the brain region(s) where seizures originate. Surgical success rates vary between 20-80% because no clinically validated biological markers of the EZ exist. Localizing the EZ is a costly and time-consuming process beginning with non-invasive neuroimaging and often followed by days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity (e.g., low-voltage high frequency activity) on individual channels occurring immediately before seizures or spikes that occur on interictal iEEG (i.e., between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in EZ localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients.

Intracranial EEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aim to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the EZ. We hypothesize that when a patient is not clinically seizing, it is because the EZ is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, patient-specific dynamical network models (DNMs) were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics (SSMs). We validated the SSMs in a retrospective analysis of 65 patients by using the SSMs of the annotated EZ to predict surgical outcomes. The SSMs predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians predictions (surgical success rate of this dataset). In failed outcomes, we identified regions of the brain with high SSMs that were untreated. When compared to high frequency oscillations, the most commonly proposed interictal iEEG feature for EZ localization, SSMs outperformed in predictive power (by a factor of 1.2) suggesting SSMs may be an interictal iEEG fingerprint of the EZ. An integrative process-based model for biomass and yield estimation of hardneck garlic (Allium sativum) We introduce an integrative process-driven crop model for garlic (Allium sativum). Building on our previous model that simulated key phenological, morphological, and physiological features of a garlic plant, the new garlic model provides comprehensive and integrative estimations of biomass accumulation and yield formation under diverse environmental conditions. This model also showcases an application of Cropbox to develop a comprehensive crop model. Cropbox is a crop modeling framework featuring declarative modeling language and unified simulation interface for building and improving crop models. Using Cropbox, we first evaluated the model performance against three datasets with an emphasis on biomass and yield measured under different environmental conditions and growing seasons. We then applied the model to simulate optimal planting dates under future climate conditions for assessing climate adaptation strategies between two contrasting locations in South Korea: the current growing region (Gosan) and an unfavorable cold winter region (Chuncheon, Gangwon-do). The model simulated the growth and development of a southern-type cultivar (Namdo, Jeju-do) reasonably well. Under RCP (Representative Concentration Pathway) scenarios, an overall delay in optimal planting date from a week to a month and a slight increase in potential yield were expected in Gosan. Expansion of growing region to northern area including Chuncheon was expected due to mild winter temperatures in the future and may allow Namdo cultivar production in more regions. The predicted optimal planting date in the new region was similar to the current growing region that favors early fall planting. Our new integrative garlic model provides mechanistic, process-driven crop responses to environmental cues and can be useful for assessing climate impacts and identifying crop specific climate adaptation strategies for the future. INPP4B drives lysosome biogenesis to restrict leukemic stem cell differentiation and promote leukemogenesis Signaling pathways that control vital features of leukemic stem cells including multipotency, self-renewal, clonal expansion and quiescence remain unclear. Emerging studies illustrate critical roles for lysosomes in hematopoietic and leukemic stem cell fate. By investigating consequences of INPP4B alterations in AML, we have discovered its role in driving leukemic  stemness. We observed that INPP4B is highly expressed leukemic stem cell populations and Inpp4b-deficeint leukemias demonstrate increased disease latency, reduced leukemia initiating potential which is associated with a differentiated leukemic phenotype. Molecular analyses show that Inpp4b-deficient leukemias have compromised lysosomal gene expression, lysosomal content, and lysosomal activity. Our discovery of a novel pathway linking INPP4B, lysosomal biogenesis and leukemic stemness, provides a mechanism to explain the association of high INPP4B expression with poor AML prognosis, and highlights novel patient stratification strategies and LSC-specific leukemic therapies.

Key PointsOur findings highlight a novel pathway linking INPP4B, lysosomal function and leukemic stemness that explains the prognostic role of INPP4B in AML.
Our data reveal the utility of INPP4B as a biomarker of aggressive AML and provide a rationale to explore INPP4B and its associated function in lysosome biology as novel strategies to target LSC and AML Discovery of a pre-mRNA structural scaffold as a contributor to the mammalian splicing code The specific recognition of splice signals at or near exon-intron junctions is not explained by their weak conservation and instead is postulated to require a multitude of features embedded in the pre-mRNA strand. We explored the possibility of three-dimensional structural scaffold of AdML - a model pre-mRNA substrate - guiding early spliceosomal components to the splice signal sequences. We find that mutations in the non-cognate splice signal sequences impede recruitment of early spliceosomal components due to disruption of the global structure of the pre-mRNA. We further find that the pre-mRNA segments potentially interacting with the early spliceosomal component U1 snRNP are distributed across the intron, that there is a spatial proximity of 5' and 3' splice sites within the pre-mRNA scaffold, and that an interplay exists between the structural scaffold and splicing regulatory elements in recruiting early spliceosomal components. These results suggest that early spliceosomal components can recognize a three-dimensional structural scaffold beyond the short splice signal sequences, and that in our model pre-mRNA, this scaffold is formed across the intron involving the major splice signals. This provides a conceptual basis to analyze the contribution of recognizable three-dimensional structural scaffolds to the splicing code across the mammalian transcriptome. Variation in female songbird state determines signal strength needed to evoke copulation It is the female response to male signals that determines courtship success. In most songbirds, females control reproduction via the copulation solicitation display (CSD), an innate, stereotyped posture produced in direct response to male displays. Because CSD can be elicited in the absence of males by the presentation of recorded song, CSD production enables investigations into the effects of underlying signal features and behavioral state on female mating preferences. Using computer vision to quantify CSD trajectory in female brown-headed cowbirds (Molothrus ater), we show that both song quality and a females internal state predict CSD production, as well as the onset latency and duration of the display. We also show that CSD can be produced in a graded fashion based on both signal strength and internal state. These results emphasize the importance of underlying receiver state in determining behavioral responses and suggest that female responsiveness acts in conjunction with male signal strength to determine the efficacy of male courtship. A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice The interaction of physical structure and nutrient loading drives ecosystem change in a large tropical lake over 40 years Many lakes across the world are entering novel states and experiencing altered biogeochemical cycling due to local anthropogenic stressors. In the tropics, understanding the drivers of these changes can be difficult due to a lack of documented historic conditions or an absence of continuous monitoring that can distinguish between intra- and inter-annual variation. Over the last forty years (1980-2020), Lake Yojoa (Honduras) has experienced increased watershed development as well as the introduction of a large net-pen Tilapia farm, resulting in a dramatic reduction in seasonal water clarity, increased trophic state and altered nutrient dynamics, shifting Lake Yojoa from an oligotrophic (low productivity) to mesotrophic (moderate productivity) ecosystem. To assess the changes that have occurred in Lake Yojoa as well as putative drivers for those changes, we compared Secchi depth (water clarity), dissolved inorganic nitrogen (DIN), and total phosphorus (TP) concentrations at continuous semi-monthly intervals for the three years between 1979-1983 and again at continuous 16-day intervals for 2018-2020. Between those two periods we observed the loss of a clear water phase that previously occurred in the months when the water column was fully mixed. Seasonal peaks in DIN coincident with mixing suggest that an enhanced accumulation of ammonium in the hypolimnion (the bottom layer of a stratified lake) during stratification, and release to the epilimnion (the top layer of a stratified lake) with mixing maintains high algal abundance and subsequently low secchi depth during what was previously the clear water phase. This interaction of nutrient loading and Lake Yojoas monomictic stratification regime illustrates a key phenomenon in how physical water column structure and nutrients interact in tropical monomictic lakes. This work highlights the need to consider nutrient dynamics of warm anoxic hypolimnions, not just surface water nutrient concentrations, to understand environmental change in these societally important but understudied ecosystems. Atomic Force Microscopy Reveals Distinct Protofilament-scale Structural Dynamics in Depolymerizing Microtubule Arrays The dynamic reorganization of microtubule-based cellular structures, such as the spindle and the axoneme, fundamentally depends on the dynamics of individual polymers within multimicrotubule arrays. A major class of enzymes, implicated in both the complete demolition and fine size control of microtubule-based arrays, are depolymerizing kinesins. How different depolymerases differently remodel microtubule arrays is poorly understood. A major technical challenge in addressing this question is that existing optical or electron-microscopy methods lack the spatial-temporal resolution to observe the dynamics of individual microtubules within larger arrays. Here we use Atomic Force Microscopy (AFM) to image depolymerizing arrays at single microtubule and protofilament resolution. We discover previously unseen modes of microtubule array destabilization by conserved depolymerases. We find that the kinesin-13 MCAK mediates asynchronous protofilament depolymerization and lattice-defect propagation, whereas the kinesin-8 Kip3p promotes synchronous protofilament depolymerization. Unexpectedly, MCAK can depolymerize the highly stable axonemal doublets, but Kip3p cannot. We propose that distinct protofilament-level activities underlie the functional dichotomy of depolymerases, resulting in either large-scale destabilization or length regulation of microtubule arrays. Our work establishes AFM as a powerful strategy to visualize microtubule dynamics within arrays and reveals how nanometer-scale substrate specificity leads to differential remodeling of micron-sized cytoskeletal structures.

SIGNIFICANCE STATEMENTOne cannot help but marvel at the precise organization of microtubule polymers in cellular structures such as the axoneme and the spindle. However, our understanding of the biochemical mechanisms that sculpt these arrays comes largely from in vitro experiments with a small number (one or two) of microtubules. This is somewhat akin to studying the architecture of multilane highways by studying one-lane streets. Here we directly visualize depolymerizing microtubule arrays at individual microtubule and protofilament resolution using Atomic Force Microscopy. Our results reveal differences in microtubule depolymerase activity and provide insights into how these differences in enzymatic activity on the nanometer scale can result in the differential remodeling of multi-microtubule arrays on the micron-length scale. Intrinsic Functional Connectivity in the Default Mode Network Predicts Mnemonic Discrimination: A Connectome-based Modeling Approach The ability to distinguish existing memories from similar perceptual experiences is a core feature of episodic memory. This ability is often examined using the Mnemonic Similarity Task in which people discriminate memories of studied objects from perceptually similar lures. Studies of the neural basis of such mnemonic discrimination have mostly focused on hippocampal function and connectivity. However, default mode network (DMN) connectivity may also support such discrimination, given that the DMN includes the hippocampus, and its connectivity supports many aspects of episodic memory. Here, we used connectome-based predictive modeling to identify associations between intrinsic DMN connectivity and mnemonic discrimination. We leveraged a wide range of abilities across healthy younger and older adults to facilitate this predictive approach. Resting-state functional connectivity in the DMN predicted mnemonic discrimination outside the MRI scanner, especially among prefrontal and temporal regions and including several hippocampal regions. This predictive relationship was stronger for younger than older adults, primarily for temporalprefrontal connectivity. The novel associations established here are consistent with mounting evidence that broader cortical networks including the hippocampus support mnemonic discrimination. They also suggest that age-related network disruptions undermine the extent that the DMN supports this ability. This study provides the first indication of how intrinsic functional properties of the DMN support mnemonic discrimination. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. The obstacles and potential clues of prime editing applications in tomato, a dicot plant Precision genome editing is highly desired for crop improvement. The recently emerged CRISPR/Cas technology offers great potential applications in precision plant genome engineering. A prime editing (PE) approach combining a reverse transcriptase (RT) with a Cas9 nickase and a "priming" extended guide RNA has shown a high frequency for precise genome modification in mammalian cells and several plant species. Nevertheless, the applications of the PE approach in dicot plants are still limited and inefficient. We designed and tested prime editors for precision editing of a synthetic sequence in a transient assay and for desirable alleles of 10 loci in tomato by stable transformation. Our data obtained by targeted deep sequencing also revealed only low PE efficiencies in both the tobacco and tomato systems. Further assessment of the activities of the PE components uncovered potential reasons for the inefficiency of the PE complexes. Modifying the pegRNA sequences by shortening or introducing mismatches to the primer binding sequences (PBS) in order to reduce their melting temperatures (Tm) did not enhance the PE efficiency at the SlBMP21, SlALC and SlALS1 loci. Our data show challenges of PE approach in tomato, indicating a further improvement of the PE system for the successful applications such as use of improved expression systems. Our work provides an important clue for the successful application of the PE approach in crop improvement. 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. 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. Analyzing Assay Specificity in Metabolomics using Unique Ion Signature Simulations Targeted, untargeted and data-independent acquisition (DIA) metabolomics workflows are often hampered by ambiguous identification based on either MS1 information alone or relatively few MS2 fragment ions. While DIA methods have been popularized in proteomics, it is less clear whether they are suitable for metabolomics workflows due to their large precursor isolation windows and complex co-isolation patterns. Here, we quantitatively investigate the conditions necessary for unique metabolite detection in complex backgrounds using precursor and fragment ion mass-to-charge separation, comparing three benchmarked MS methods (MS1, MRM, DIA). Our simulations show that DIA outperformed MS1-only and MRM-based methods with regards to specificity by a factor of ~2.8-fold and ~1.8-fold, respectively. Additionally, we show that our results are not dependent on the number of transitions used or the complexity of the background matrix. Finally, we show that collision energy is an important factor in unambiguous detection and that a single collision energy setting per compound cannot achieve optimal pairwise differentiation of compounds. Our analysis demonstrates the power of using both high resolution precursor and high resolution fragment ion m/z for unambiguous compound detection. This work also establishes DIA as an emerging MS acquisition method with high selectivity for metabolomics, outperforming both DDA and MRM with regards to unique compound identification potential.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/434579v2_ufig1.gif" ALT="Figure 1">
View larger version (23K):
org.highwire.dtl.DTLVardef@142b100org.highwire.dtl.DTLVardef@1728a1corg.highwire.dtl.DTLVardef@c953c8org.highwire.dtl.DTLVardef@19b856a_HPS_FORMAT_FIGEXP  M_FIG C_FIG Loss of SUMO-specific protease 2 causes isolated glucocorticoid deficiency by blocking adrenal cortex zonal transdifferentiation SUMOylation is a dynamic posttranslational modification, that provides fine-tuning of protein function involved in the cellular response to stress, differentiation, and tissue development. In the adrenal cortex, an emblematic endocrine organ that mediates adaptation to physiological demands, the SUMOylation gradient is inversely correlated with the gradient of cellular differentiation raising important questions about its role in functional zonation and the response to stress. Considering that SUMO-specific protease 2 (SENP2), a deSUMOylating enzyme, is upregulated by ACTH/PKA signalling within the zona Fasciculata (zF), we generated mice with adrenal-specific Senp2 loss to address these questions. Disruption of SENP2 activity in steroidogenic cells leads to specific hypoplasia of the zF, a blunted reponses to ACTH and isolated glucocorticoid deficiency. Mechanistically, overSUMOylation resulting from SENP2 loss shifts the balance between ACTH/PKA and WNT/{beta}-catenin signalling leading to repression of PKA activity and ectopic activation of {beta}-catenin. At the cellular level, this blocks transdifferentiation of {beta}-catenin-positive zona Glomerulosa cells into zF cells and sensitises them to premature apoptosis. Our findings indicate that the SUMO pathway is critical for adrenal homeostasis and stress responsiveness. A Facile Alternative Sustainable Process for the Extraction and Purification of Microbial Melanin Conventional techniques for the extraction of the melanin encounter several disadvantages such as poor extraction efficiency, excessive use of acid and alkali, and lengthy time duration. To extract melanin in a more sustainable manner, herein suitability of an aqueous solution of quaternary ammonium hydroxide known as tetrabutylammonium hydroxide (40% w/w TBAOH in water) to extract and purify the pigment from the endophyte Streptomyces hyderabadensis 7VPT5-5R was investigated. The solvent could extract 5.54{+/-}0.03 g/L of pure melanin against 3.31{+/-} 0.02 g/L of pure melanin by conventional method from bacterial culture resulting 66% increase in the yield of the pigment. The quaternary ammonium based solvent was further recycled for 5 consecutive cycles and production of melanin with yield ranging from 5.54{+/-}0.03 g/L to 5.47{+/-} 0.02 g/L was obtained. The yield of the pigment was 38-40% higher in the recycled solvent in comparison to the melanin yield extracted by conventional method. Considering the efficiency of the solvent for effective extraction and purification of melanin and its recyclability potential, it can be considered as a sustainable solvent for the extraction of the pigments from bacterial culture. Furthermore, the developed method for extraction of melanin from microorganisms as a sustainable source would help in reducing the cost of melanin leading to its efficient utilization in diverse fields. Mechanisms Underlying WNT-mediated Priming of Human Embryonic Stem Cells Embryogenesis is guided by a limited set of signaling pathways dynamically expressed in different places. How a context dependent signaling response is generated has been a central question of developmental biology, which can now be addressed with in vitro models of human embryos that are derived from embryonic stem cells (hESCs) called gastruloids. Our previous work demonstrated that during early self-organization of gastruloids, cells chronicle signaling hierarchy. Only cells that have been exposed (primed) by WNT signaling can respond to subsequent Activin exposure and differentiate to mesendodermal (ME) fates. Here, we show that WNT priming does not alter SMAD2 binding nor its chromatin opening, but rather, acts by inducing the expression of the SMAD2 co-factor, EOMES. Expression of EOMES is sufficient to replace WNT upstream of Activin-mediated ME differentiation, thus unveiling the mechanistic basis for priming and cellular memory in early development.