Embedded 3D printing in self-healing annealable composites for precise patterning of functionally mature human neural constructs Human in vitro models of neural tissue with controllable cellular identity, tunable microenvironment, and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing in jammed microgel supports (i.e., granular gels) holds great promise as it allows precise and programmable patterning of extremely soft and compliant tissue constructs. However, in contrast to the vast material landscape available for bulk hydrogels, granular printing support formulations are restricted to a handful of materials without the ability for facile adjustment of biofunctional properties of the cellular microenvironment. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, we present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise freeform patterning of human stem cells and consequent generation and long-term maintenance of mature subtype-specific neurons that extend projections within the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular channels. Due to its modularity, SHAPE biomanufacturing toolbox not only offers a solution for functional modeling of mechanically sensitive neural constructs, but also has potential to be applied to a wide range of biomaterials with different crosslinking mechanisms to model tissues and diseases where recapitulation of complex architectural features and topological cues is essential.
Extracellular Vesicle (EV) Mitochondria and EV/HSP27 Mixtures Protect the Ischemic Brain Endothelium Ischemic stroke causes brain endothelial cell (BEC) death and damages tight junction integrity of the blood-brain barrier (BBB). We harnessed the innate mitochondrial load of endothelial cell-derived extracellular vesicles (EVs) and utilized mixtures of EV/exogenous heat shock protein 27 (HSP27) as a one-two punch strategy to increase BEC survival (via EV mitochondria) and preserve their tight junction integrity (via HSP27 effects). We demonstrated that the medium-to-large (m/lEV) but not small EVs (sEV) transferred their mitochondrial load, which subsequently colocalized with the mitochondrial network of the recipient primary human BECs. BECs treated with m/lEVs increased relative ATP levels and displayed superior mitochondrial function. m/lEVs isolated from rotenone (mitochondrial complex I inhibitor) exposed BECs (RTN-m/lEVs) did not increase BECs ATP levels compared to naive m/lEVs. In contrast, RTN-sEVs functionality was minimally affected compared to naive sEVs. Compared to EV/HSP27 mixtures, PEG-DET/EV/HSP27 ternary mixtures increased HSP27 protein loading. (PEG-DET/HSP27)/EV ternary and EV/HSP27 binary mixtures decreased the paracellular permeability of small and large molecular mass fluorescent tracers in oxygen glucose-deprived primary human BECs. This one-two punch approach to increase BEC metabolic function and tight junction integrity is a promising strategy for BBB protection and prevention of long-term neurological dysfunction post-ischemic stroke.

Highlights[tpltrtarr] Medium-to-large extracellular vesicles (m/lEVs), not small EVs contain mitochondria
[tpltrtarr]m/lEVs increased ATP and mitochondrial function in brain endothelial cells (BECs)
[tpltrtarr]Donor m/lEV mitochondria colocalized with host mitochondria in recipient BECs
[tpltrtarr]m/lEVs from rotenone-exposed BECs did not increase recipient BEC ATP levels
[tpltrtarr]PEG-DET/EV/HSP27 ternary mixtures increase exogenous HSP27 protein loading


Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/466491v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@155f618org.highwire.dtl.DTLVardef@8fa778org.highwire.dtl.DTLVardef@13bd44aorg.highwire.dtl.DTLVardef@ee771e_HPS_FORMAT_FIGEXP  M_FIG C_FIG
Leaf Aqueous Extract of Manilkara hexandra influenced Glucose Metabolism in fish: An observation with Labeo rohita Fingerlings as model organism Manilkara hexandra (Roxb.) Dubard (common name Khirni, family: Sapotaceae) is an evergreen traditionally used medicinal plant. The present study aimed to see the effects of leaf aqueous extract of M. hexandra (LAEMH) on digestive and glucose metabolic enzyme action and serum glucose level in rohu, Labeo rohita, fingerlings. Experimental fish were fed a basal diet (Group I), and diets supplemented with LAEMH at 300 mg (Group II) and 600 mg (Group III) kg-1body weight. A significant reduction in serum glucose was noticed in the treated groups when compared with the control group. The reduced amylase activity was noticed in the treated fingerlings in a dose-dependent manner. However, lipase and protease activities didnt differ significantly among the experimental groups. Reduced serum glucose level might be correlated with the decline in the activity of digestive amylase in fish. Group II (3.35{+/-}0.19 U) and Group III (3.49{+/-}0.13 U) were recorded with reduced glucose-6-phosphatase activities than the control group (4.4{+/-}0.39 U). Moreover, the study revealed a decline in fructose-1,6-phosphatase activities in the treated groups in comparison to the control group. The decline in the activities of the metabolic enzymes might be associated with the non-availability of glucose owing to reduced activity of the digestive amylase in the treated groups. In conclusion, the present study established the hypoglycaemic effect of the leaf aqueous extract of M. hexandra in a fish model. RSC and GRFs confer promoter directionality by limiting divergent noncoding transcription The directionality of gene promoters - the ratio of protein-coding over divergent noncoding transcription - is highly variable and regulated. How promoter directionality is controlled remains poorly understood. Here, we show that the chromatin remodelling complex RSC and general regulatory factors (GRFs) dictate promoter directionality by attenuating divergent transcription. At gene promoters that are highly directional, depletion of RSC leads to a relative increase in divergent noncoding transcription and thus a decrease in promoter directionality. We find that RSC facilitates nucleosome positioning upstream in promoters at the sites of divergent transcription. These highly directional promoters are also enriched for the binding of GRFs such as Reb1 and Abf1. Ectopic targeting of divergent transcription initiation sites with GRFs or the dCas9 protein suppresses divergent transcription. Our data suggest that RSC and GRFs play a pervasive role in limiting divergent transcription. We propose that any DNA binding factor, when stably associated with cryptic transcription start sites, form barriers for repressing divergent transcription. Our study provides an explanation as to why certain promoters are more directional than others. The genetic basis of interspecies cooperation and conflict in naturally-occurring isolates of a model plant symbiont Given the need to predict the outcomes of evolution in host-associated microbiomes, whether microbial and host fitnesses tend to trade off, generating conflict, remains a pressing question. Examining the relationships between host and microbe fitness proxies at both the phenotypic and genomic levels can illuminate the mechanisms underlying interspecies cooperation and conflict. We conducted genome-wide association studies (GWAS) to examined naturally-occurring genetic variation in 191 strains of the model microbial symbiont, Ensifer meliloti, paired with each of two host Medicago truncatula genotypes in single- or multi-strain experiments. Using this data, we determine how multiple proxies of microbial and host fitness were related to one another and test key predictions about mutualism evolution at the genomic scale, while also addressing the challenge of measuring microbial fitness. We found little evidence for interspecies fitness conflict; loci tended to have concordant effects on both microbe and host fitnesses, even in environments with multiple co-occurring microbes. Our results emphasize the importance of quantifying microbial relative fitness for understanding microbiome evolution and thus harnessing microbiomes to improve host fitness. Additionally, we find that mutualistic coevolution between hosts and microbes potentially acts to maintain, rather than erode, genetic diversity, thus, explaining why variation in mutualism traits persists in nature. Assessing the impact of grassland management on landscape multifunctionality Land-use intensification has contrasting effects on different ecosystem services, often leading to land-use conflicts. While multiple studies have demonstrated how landscape-scale strategies can minimise the trade-off between agricultural production and biodiversity conservation, little is known about which land-use strategies maximise the landscape-level supply of multiple ecosystem services (landscape multifunctionality), a common goal of stakeholder communities.

We combine comprehensive data collected from 150 German grassland sites with a simulation approach to identify landscape compositions, with differing proportions of low-, medium-, and high-intensity grasslands, that minimise trade-offs between the six main grassland ecosystem services prioritised by local stakeholders: biodiversity conservation, aesthetic value, productivity, carbon storage, foraging, and regional identity. Results are made accessible through an online tool that provides information on which compositions best meet any combination of user-defined priorities (https://neyret.shinyapps.io/landscape_composition_for_multifunctionality/).

Results show that an optimal landscape composition can be identified for any pattern of ecosystem service priorities. However, multifunctionality was similar and low for all landscape compositions in cases where there are strong trade-offs between services (e.g. aesthetic value and fodder production), where many services were prioritised, and where drivers other than land use played an important role. We also found that if moderate service levels are deemed acceptable, then strategies in which both high and low intensity grasslands are present can deliver landscape multifunctionality. The tool presented can aid informed decision-making by predicting the impact of future changes in landscape composition, and by allowing for the relative roles of stakeholder priorities and biophysical trade-offs to be understood by scientists and practitioners alike.

HighlightsO_LIAn online tool identifies optimal landscape compositions for desired ecosystem services
C_LIO_LIWhen the desired services are synergic, the optimum is their common best landscape composition
C_LIO_LIWhen the desired services trade-off, a mix of grassland intensity is most multifunctional
C_LIO_LISuch tools could support decision-making processes and aid conflict resolution
C_LI

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/208199v5_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@3273f6org.highwire.dtl.DTLVardef@5b3a5aorg.highwire.dtl.DTLVardef@153f526org.highwire.dtl.DTLVardef@103cbea_HPS_FORMAT_FIGEXP  M_FIG C_FIG 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. Learning interpretable cellular responses tocomplex perturbations in high-throughput screens Recent advances in multiplexed single-cell transcriptomics experiments are facilitating the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible, so computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA encodes and learns transcriptional drug responses across different cell type, dose, and drug combinations. The model produces easy-to-interpret embeddings for drugs and cell types, which enables drug similarity analysis and predictions for unseen dosage and drug combinations. We show that CPA accurately models single-cell perturbations across compounds, doses, species, and time. We further demonstrate that CPA predicts combinatorial genetic interactions of several types, implying that it captures features that distinguish different interaction programs. Finally, we demonstrate that CPA can generate in-silico 5,329 missing genetic combination perturbations (97.6% of all possibilities) with diverse genetic interactions. We envision our model will facilitate efficient experimental design and hypothesis generation by enabling in-silico response prediction at the single-cell level, and thus accelerate therapeutic applications using single-cell technologies. Chromosome counting in the mouse zygote using low-invasive super-resolution live-cell imaging In preimplantation embryos, an abnormal chromosome number causes developmental failure and a reduction in the pregnancy rate. Conventional chromosome testing methods requiring biopsy reduce the risk of associated genetic diseases; nevertheless, the reduction in cell number also reduces the pregnancy rate. Therefore, we attempted to count the chromosomes in mouse (Slc:ICR) embryos using super-resolution live-cell imaging as a new method of chromosome counting that does not reduce the cell number or viability. We counted the forty chromosomes at the first mitosis by injecting embryos with histone H2B-mCherry mRNA under conditions by which pups could be obtained; however, the results were often an underestimation of chromosome number and varied by embryo and time point. Therefore, we developed a method to count the chromosomes via CRISPR/dCas-mediated live-cell fluorescence in situ hybridization targeting the sequence of the centromere region, enabling us to count the chromosomes more accurately in mouse embryos. The methodology presented here may provide useful information for assisted reproductive technologies, such as those used in livestock animals/humans, as a technique for assessing the chromosomal integrity of embryos prior to transfer.

Impact StatementLow-toxic super-resolution observation enables chromosome counting in preimplantation embryos without cell collection. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Stroke-related alterations ininter-areal communication Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned. Mutagenic distinction between the receptor-binding and fusion subunits of the SARS-CoV-2 spike glycoprotein and its upshot We observe that a residue R of the spike glycoprotein of SARS-CoV-2 which has mutated in one or more of the current Variants of Concern or Interest or under Monitoring rarely participates in a backbone hydrogen bond if R lies in the S1 subunit and usually participates in one if R lies in the S2 subunit. A partial explanation for this based upon free energy is explored as a potentially general principle in the mutagenesis of viral glycoproteins. This observation could help target future vaccine cargos for the evolving coronavirus as well as more generally. A study of the Delta and Omicron variants suggests that Delta was an energetically necessary intermediary in the evolution from Wuhan-Hu-1 to Omicron. Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding. A multi-dimensional integrative scoring framework for predicting functional variants in the human genome Attempts to identify and prioritize functional DNA elements in coding and noncoding regions, particularly through use of in silico functional annotation data,continue to increase in popularity. However, specific functional roles may vary widely from one variant to another, making it challenging to summarize different aspects of variant function. Here we propose Multi-dimensional Annotation Class Integrative Estimation (MACIE), an unsupervised multivariate mixed model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and noncoding variants. Unlike existing one-dimensional scoring methods, MACIE views variant functionality as a composite attribute encompassing multiple characteristics, and estimates the joint posterior functional probability vector of each genomic position, a quantity that offers richer and more interpretable information in the presence of multiple aspects of functionality. Applied to a variety of independent coding and non-coding datasets, MACIE demonstrates powerful and robust performance in discriminating between functional and non-functional variants. We also show an application of MACIE to fine-mapping using lipids GWAS summary statistics data from the European Network for Genetic and Genomic Epidemiology Consortium. Revealing the inherent susceptibility of pathogenic bacteria to magnetic hyperthermia The growing number of multiple drug resistant (MDR) bacteria and the dwindling pipeline of new antibiotics are driving us towards a  post-antibiotic era in which even common infections would become difficult to treat. To address this, an antibiotic-free strategy that can combat multiple bacteria is recommended. Most of the proposed approaches nevertheless have several limitations, including bacterial targeting. To overcome such limitations, the proposed strategy employs the bacterial machinery to self-destruct. Herein, the biosynthesis of magnetic nanoparticle (MNP) is reported for the first time in multiple pathogenic bacteria, including MDR bacteria. The intracellular MNPs composed of superparamagnetic zinc ferrites were formed in presence of iron and zinc precursors. Exposure of the treated bacteria/biofilms to an alternating magnetic field (AMF) exhibited hyperthermia (5-6{degrees}C) and a dramatic decrease in bacterial viability, suggesting the MNPs therapeutic potential. Likewise, the bacteria existing in vivo biosynthesize the MNPs by mining these elements from the host. To determine its therapeutic efficacy, the infected tissues were exposed directly to AMF. A 3-4 log reduction in bacterial burden, as compared to antibiotics treatment, confirmed the significance of using naturally existing MNPs to combat bacterial infections. The proposed broad-spectrum approach can therefore aid in overcoming the challenges facing anti-bacterial therapies. An exon-intron split framework to prioritize miRNA-driven post-transcriptional regulatory signals and its application to study energy homeostasis in pigs The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses. Survival Genie, a web platform for survival analysis across pediatric and adult cancers. The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-Seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-Seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile.

The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/. PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized.

HighlightsO_LIWe present PySTACHIO, a refined version of our spot tracking algorithm
C_LIO_LIWe demonstrate highly improved performance over previous MATLAB versions
C_LIO_LIPySTACHIO can accurately estimate stoichiometries and 2D diffusion coefficients
C_LIO_LIPerformance is comparable to state-of-the-art packages on challenge data
C_LIO_LIPySTACHIO has both GUI and command line interfaces and can be hosted as a web app
C_LI

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/435952v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@17cc45dorg.highwire.dtl.DTLVardef@3fb66eorg.highwire.dtl.DTLVardef@e20360org.highwire.dtl.DTLVardef@4ba47d_HPS_FORMAT_FIGEXP  M_FIG C_FIG Allopurinol Blocks The Formation And Progression Of Aortic Aneurysm In A Mouse Model Of Marfan Syndrome 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

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org.highwire.dtl.DTLVardef@eab02aorg.highwire.dtl.DTLVardef@1d3b39eorg.highwire.dtl.DTLVardef@1b54d0forg.highwire.dtl.DTLVardef@1d61ad0_HPS_FORMAT_FIGEXP  M_FIG C_FIG 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. RESTORING GLUTAMATE RECEPTOR SIGNALING IN PANCREATIC ALPHA CELLS RESCUES GLUCAGON RESPONSES IN TYPE 1 DIABETES Glucagon secretion from pancreatic alpha cells is crucial to prevent hypoglycemia. For reasons still unknown, people with type 1 diabetes lose this glucoregulatory mechanism and are susceptible to dangerous hypoglycemia. Here we show that alpha cells in living pancreas slices from donors with type 1 diabetes failed to secrete glucagon in response to decreases in glucose concentration, thus mirroring the in vivo unresponsiveness to hypoglycemia. Glucagon content and responses to KCl depolarization were not affected, suggesting that alpha cells retained their secretory potential. By contrast, alpha cells had severely impaired signaling via glutamate receptors of the AMPA/kainate type. Under healthy conditions, activating these receptors was required to elicit full glucagon responses to decreases in glucose levels. In type 1 diabetes, reactivating residual glutamate receptor function with the positive allosteric modulators cyclothiazide and aniracetam restored glucagon secretion in response to hypoglycemia. These positive allosteric modulators are already approved to treat other conditions and could be repurposed to prevent hypoglycemia and improve management of diabetes. DOMINANT AWN INHIBITOR encodes the ALOG protein originating from gene duplication and inhibits awn elongation by suppressing cell proliferation and elongation in sorghum The awn, a needle-like structure extending from the tip of the lemma in grass species, plays a role in environmental adaptation and fitness. In some crops, awns appear to have been eliminated during domestication. Although numerous genes involved in awn development have been identified, several dominant genes that eliminate awns are also known to exist. For example, in sorghum (Sorghum bicolor), the dominant awn inhibiting gene has been known since 1921; however, its molecular features remain uncharacterized. In this study, we conducted quantitative trait locus analysis and a genome-wide association study of awn-related traits in sorghum and identified DOMINANT AWN INHIBITOR (DAI), which encodes the ALOG family protein on chromosome 3. DAI appeared to be present in most awnless sorghum cultivars, likely because of its effectiveness. Detailed analysis of the ALOG protein family in cereals revealed that DAI originated from duplication of its twin paralog (DAIori) on chromosome 10. Observations of immature awns in near-isogenic lines revealed that DAI inhibits awn elongation by suppressing both cell proliferation and elongation. We also found that only DAI gained a novel function to inhibit awn elongation through an awn-specific expression pattern distinct from that of DAIori. Interestingly, heterologous expression of DAI with its own promoter in rice inhibited awn elongation in the awned cultivar Kasalath. We found that DAI originated from gene duplication, providing an interesting example of gain-of-function that occurs only in sorghum but shares its functionality with rice and sorghum. Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns It has been stated that in human migratory behavior, the step length series may have temporal correlation and that there is some relationship between this time dependency and the fact that the frequency distribution of step length follows a power-law distribution. Furthermore, the frequency of occurrence of the step length in some large marine organisms has been found to switch between power-law and exponential distributions, depending on the difficulty of prey acquisition. However, to date it has not been clarified how the aforementioned three phenomena arise: the positive correlation created in the step length series, the relation between the positive correlation of the step length series and the form of an individuals step length distribution, and the switching between power-law and exponential distributions depending on the abundance of prey. This study simulated foraging behavior using the Bayesian decision-making agent simultaneously performing both knowledge learning and knowledge-based inference to analyze how the aforementioned three phenomena arise. In the agent with learning and inference, past experiences were stored as hypotheses (knowledge) and they were used in current foraging behavior; at the same time, the hypothesis continued to be updated based on new experiences. The simulation results show that the agent with both learning and inference has a mechanism that simultaneously causes all the phenomena. Structural predictions of the SNX-RGS proteins suggest they belong to a new class of lipid transfer proteins Recent advances in protein structure prediction using machine learning such as AlphaFold2 and RosettaFold presage a revolution in structural biology. Genome-wide predictions of protein structures are providing unprecedented insights into their architecture and intradomain interactions, and applications have already progressed towards assessing protein complex formation. Here we present detailed analyses of the sorting nexin proteins that contain regulator of G-protein signalling domains (SNX-RGS proteins), providing a key example of the ability of AlphaFold2 to reveal novel structures with previously unsuspected biological functions. These large proteins are conserved in most eukaryotes and are known to associate with lipid droplets (LDs) and sites of LD-membrane contacts, with key roles in regulating lipid metabolism. They possess five domains, including an N-terminal transmembrane domain that anchors them to the endoplasmic reticulum, an RGS domain, a lipid interacting phox homology (PX) domain and two additional domains named the PXA and PXC domains of unknown structure and function. Here we report the crystal structure of the RGS domain of sorting nexin 25 (SNX25) and show that the AlphaFold2 prediction closely matches the experimental structure. Analysing the full-length SNX-RGS proteins across multiple homologues and species we find that the distant PXA and PXC domains in fact fold into a single unique structure that notably features a large and conserved hydrophobic pocket. The nature of this pocket strongly suggests a role in lipid or fatty acid binding, and we propose that these molecules represent a new class of conserved lipid transfer proteins. Vitronectin acts as a key regulator of adhesion and migration in human umbilical cord-derived MSCs under different stress conditions Mesenchymal stem cell (MSC)-based therapy gets compromised as adverse microenvironmental conditions like nutrient deprivation, ischemia, hypoxia at the target site affect migration, engraftment and viability, of MSCs post transplantation. To improve the treatment efficacy, it is critical to identify factors involved in regulating migration and adhesion of MSCs under such microenvironmental stress conditions. In our study, we observed that human Whartons jelly-derived MSCs (WJ-MSCs) exhibited increase in cell spread area and adhesion, with reduction in cellular migration under serum starvation stress. The changes in adhesion and migration characteristics were accompanied by formation of large number of super mature focal adhesions along with extensive stress fibres and altered ECM gene expression with notable induction in vitronectin (VTN) expression. NF-{kappa}{beta} was found to be a positive regulator of VTN expression while ERK pathway regulated it negatively. Molecular and phenotypic comparison studies with inhibition of these signalling pathways or knocking down of VTN under serum starvation established the correlation between increase in VTN expression and increased cellular adhesion with corresponding reduction in cell migration. VTN knockdown also resulted in reduction of super mature focal adhesions and extensive stress fibres, which were formed under serum starvation. Additionally, VTN induction was not detected in hypoxia-treated WJ-MSCs, and the MSCs showed no significant change in the adhesion or migration properties under hypoxia. However, when VTN expression was induced under hypoxia by ERK pathway inhibition, similar increase in cell spread area and adhesion were observed. Our study thus highlights VTN as a key player which is induced under serum starvation stress and possibly regulates the adhesion and migration properties of WJ-MSCs via focal adhesion signalling. Ribosome actuator via the SpoT/ppGpp pathway to mitigate gene overexpression burden Gene overexpression causes a burden on ribosomes, which decreases the expression of other genes and growth rate. Here, we engineer a genetic ribosome actuator that increases gene expression rate and growth rate by over 150% and 80%, respectively. The actuator expresses the hydrolysis domain of the SpoT enzyme (SpoTH) in a bacterial strain with high basal levels of ppGpp, thus increasing ribosome availability. We use this actuator in a feedforward control arrangement, wherein SpoTH is co-expressed with a gene of interest (GOI). Without SpoTH co-expression, activation of the GOI decreases the expression of a constitutive gene and growth rate by over 80% and 40%, respectively. By contrast, with SpoTH co-expression, the ribosome binding site (RBS) of SpoTH can be tuned to achieve inappreciable change of either the expression of the constitutive gene or growth rate when the GOI is activated to the same level. We finally employ the actuator to keep growth rate constant while expressing dCas9 to a level that would otherwise decrease growth rate by more than 40% due to toxicity. This actuator will be relevant in applications where high cellular protein concentrations are desired without growth defects or global reduction of gene expression.