RNAi screen of RING/U-box domain ubiquitin ligases identifies critical regulators of tissue regeneration in planarians Regenerative processes depend on the interpretation of signals to coordinate cell behaviors. The role of ubiquitin-mediated signaling is known to be important in many cellular and biological contexts, but its role in regeneration is not well understood. To investigate how ubiquitylation impacts tissue regeneration in vivo, we are studying planarians that are capable of regenerating after nearly any injury using a population of stem cells. Here we used RNAi to screen RING/U-box E3 ubiquitin ligases that are highly expressed in planarian stem cells and stem cell progeny. RNAi screening identified nine genes with functions in regeneration, including the spliceosomal factor prpf19 and histone modifier rnf2; based on their known roles in developmental processes, we further investigated these two genes. We found that prpf19 was required for animal survival but not for stem cell maintenance, suggesting a role in promoting cell differentiation. Because RNF2 is the catalytic subunit of the Polycomb Repressive Complex 1 (PRC1), we also examined other putative members of this complex (CBX and PHC). We observed a striking phenotype of regional tissue misspecification in cbx and phc RNAi planarians. To identify genes regulated by PRC1, we performed RNA-seq after knocking down rnf2 or phc. Although these proteins are predicted to function in the same complex, we found that the set of genes differentially expressed in rnf2 versus phc RNAi were largely non-overlapping. Using in situ hybridization, we showed that rnf2 regulates gene expression levels within a tissue type, whereas phc is necessary for the spatial restriction of gene expression, findings consistent with their respective in vivo phenotypes. This work not only uncovered roles for RING/U-box E3 ligases in stem cell regulation and regeneration, but also identified differential gene targets for two putative PRC1 factors required for maintaining cell-type-specific gene expression in planarians.
A constraints-based theory of the primary cause of senescence: imbalance of epigenetic and non-epigenetic information in histone crosstalk Cellular aging has been progressively elucidated by science. However, the fundamental cause of senescence--i.e., why organisms age at the multicellular-individual level--remains unclear. A recent theory of individuated multicellularity describes the emergence and growth of crucial information content for cell differentiation. This information is mostly conveyed in the non-epigenetic (i.e., transcription uncorrelated) histone crosstalk near transcription start sites. According to this theory, the non-epigenetic content emerges and grows at the expense of the information capacity for epigenetic content. If this "reassignment" of information capacity continues after adulthood, it may explain the senescence phenomenon. Here, I present a novel, falsifiable theory describing an uninterrupted growth of capacity for non-epigenetic information at the expense of that for epigenetic information not only during ontogeny but also throughout adulthood. As a byproduct, this continuous "reassignment" of capacity effectively creates an information imbalance in histone crosstalk, which in turn overregulates transcriptional levels. This overregulation is to be understood as transcriptional levels becoming more and more accurate but also less and less precise with respect to the needs of the multicellular individual--up to the point of dysfunctionality. This epigenetic/non-epigenetic information imbalance is proposed to be the primary reason why individuated multicellular organisms senesce.
OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior Representational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational (dis-)similarity matrices (RDM or RSM), which characterize the pairwise (dis-)similarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This  equal weights assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, in case of model comparison, may lead them to select an inferior model. The aim of this work is twofold: First, we sought to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RSM correspondence and affects model selection. Previous work suggested that reweighting can improve model selection in RSA but it has remained unclear to what extent these results generalize across datasets and data modalities. To draw more general conclusions, we utilized a range of publicly available datasets and three popular deep neural networks (DNNs). Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We found that reweighting individual model units markedly improved the fit between model RSMs and target RSMs derived from several fMRI and behavioral datasets and affected model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RSM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally show that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain, and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the correspondence between representational spaces. Synthetic Cooling Agents in US-marketed E-cigarette Refill Liquids and Popular Disposable E-cigarettes: Chemical Analysis and Risk Assessment. BackgroundMenthol, through its cooling and pleasant sensory effects, facilitates smoking and tobacco product initiation, resulting in the high popularity of mint/menthol-flavored E-cigarettes. More recently, E-cigarette vendors started marketing synthetic cooling agents as additives that impart a cooling effect but lack a characteristic minty odor. Knowledge about content of synthetic coolants in US-marketed E-cigarette products and associated health risks is limited.

MethodsE-liquid vendor sites were searched with the terms "koolada", "kool/cool", "ice", or WS-3/WS-23, denoting individual cooling agents, and relevant refill E-liquids were purchased. "Ice" flavor varieties of Puffbar, the most popular disposable E-cigarette brand, were compared with non-"Ice" varieties. E-liquids were characterized, and synthetic coolants quantified using GC/MS. Margin of exposure (MOE), a risk assessment parameter, was calculated to assess the risk associated with synthetic coolant exposure from E-cigarette use.

ResultsWS-3 was detected in 24/25 refill E-liquids analyzed. All Puffbar flavor varieties contained either WS-23 (13/14) or WS-3 (5/14), in both "Ice"- and non-"Ice" flavors. Modeling consumption of WS-3 from vaped E-liquids, resulted in MOEs below the safe margin of 100 for most daily use scenarios. MOEs for WS-23 were <100 for 10/13 Puffbar flavors in all use scenarios. Puffbar power specifications are identical to Juul devices.

ConclusionsSynthetic cooling agents (WS-3/WS-23) were present in US-marketed E-cigarettes, at levels that may result in consumer exposures exceeding safety thresholds set by regulatory agencies. Synthetic coolants are not only found in mint-or menthol-flavored products, but also in fruit- and candy-flavored products, including popular disposable E-cigarette products such as Puffbar.

ImplicationsSynthetic cooling agents are widely used in "kool/cool"- and "ice"-flavored E-liquids and in E-liquids without these labels, both as a potential replacement for menthol or to add cooling  notes to non-menthol flavors. These agents may be used to bypass current and future regulatory limits on menthol content in tobacco products, and not just E-cigarettes. Since synthetic cooling agents are odorless, they may not fall under the category of "characterizing flavor", potentially circumventing regulatory measures based on this concept. Regulators need to consider the additional health risks associated with exposure to synthetic cooling agents. Lower limb in sprinters with larger relative mass but not larger normalized moment of inertia Inhomogeneous muscle hypertrophy in response to daily motor executions is a morphological adaptation in humans. Inhomogeneous morphological adaptation would change the mass distribution, which in turn may affect the mechanical difficulty in moving from an inertia perspective; however, the morphological adaptation from the inertia perspective has not been examined. Here we show no corresponding differences in the normalized mass and normalized moment of inertia between the sprinters and the untrained non-sprinters. We analyzed the fat- and water-separated magnetic resonance images from the lower limbs of 11 male sprinters (100 m best time of 10.44-10.83 s) and 12 untrained non-sprinters. The lower-limb relative mass was significantly larger in sprinters (18.7{+/-}0.7% body mass) than in non-sprinters (17.6{+/-}0.6% body mass), while the normalized moment of inertia of the lower limb around the hip in the anatomical position was similar between them (0.044{+/-}0.002 vs. 0.042{+/-}0.002 [a. u.]). The thigh relative mass in sprinters (12.9{+/-}0.4% body mass) was significantly larger than that in non-sprinters (11.9{+/-}0.4% body mass), whereas the shank and foot relative masses were similar. We revealed that the adaptation to sprinting in humans does not relatively increase the mechanical difficulty to swing the lower limb in terms of inertia, even though the lower-limb mass increases, reflecting muscular hypertrophy. This is suggested to be one of the significant advantages of human morphology for adaptability to explosive motor tasks.

NEW & NOTEWORTHYWe compared the lower-limb inertia properties between male sprinters and untrained non-sprinters by using the fat- and water-separated magnetic resonance images. Sprinters had lower limbs with a larger relative mass but not a larger normalized moment of inertia than non-sprinters. We suggest one of the practical advantages of human morphological characteristics for their adaptation to explosive motor tasks, which provides a novel perspective to the literature for understanding human morphological adaptability. Protein sequence sampling and prediction from structural data The increasing integration between protein engineering and machine learning has led to many interesting results. A problem still to solve is to evaluate the likelihood that a sequence will fold into a target structure. This problem can be also viewed as sequence prediction from a known structure.

In the current work, we propose improvements in the recent architecture of Geometric Vector Perceptrons [1] in order to optimize the sampling of sequences from a known backbone structure. The proposed model differs from the original in that there is: (i) no updating in the vectorial embedding, only in the scalar one, (ii) only one layer of decoding. The first aspect improves the accuracy of the model and reduces the use of memory, the second allows for training of the model with several tasks without incurring data leakage.

We treat the trained classifier as an Energy-Based Model and sample sequences by sampling amino acids in a non-autoreggresive manner in the empty positions of the sequence using energy-guided criteria and followed by random mutation optimization. We improve the median identity of samples from 40.2% to 44.7%.

An additional question worth investigating is whether sampled and original sequences fold into similar structures independent of their identity. We chose proteins in our test set whose sampled sequences show low identity (under 30%) but for which our model predicted favorable energies. We used AlphaFold [2, 3] and observed that the predicted structures for sampled sequences highly resemble the predicted structures for original sequences, with an average TM-score of 0.84. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. Identifying and correcting multiple sources of misspecification in GWAS summary statistics for polygenic scores Publicly available genome-wide association studies (GWAS) summary statistics exhibit uneven quality, which can impact the validity of follow-up analyses. First, we present an overview of possible misspecifications that come with GWAS summary statistics. Then, in both simulations and real data analyses, we show that additional information such as imputation INFO scores, allele frequencies, and per-variant sample sizes in GWAS summary statistics can be used to detect possible issues and correct for misspecifications in the GWAS summary statistics. One important motivation for us is to improve the predictive performance of polygenic scores built from these summary statistics. Unfortunately, due to the lack of reporting standards for GWAS summary statistics, this additional information is not systematically reported. We also show that using well-matched LD references can improve model fit and translate into more accurate prediction. Finally, we discuss how to make polygenic score methods such as lassosum and LDpred2 more robust to these misspecifications to improve their predictive power. 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. Darting across space and time: Parametric modulators of sex-biased conditioned fear responding Pavlovian fear conditioning is a widely used behavioral paradigm for studying associative learning in rodents. Despite early recognition that subjects may engage in a variety of both conditioned and unconditioned responses, the last several decades have seen the field narrow its focus to measure freezing as the sole indicator of conditioned fear. We previously reported that female rats were more likely than males to engage in darting, an escape-like conditioned response that is associated with heightened shock reactivity. To determine how experimental parameters contribute to the frequency of darting in both males and females, we manipulated factors such as chamber size, shock intensity, and number of trials. To better capture fear-related behavioral repertoires in our animals, we developed ScaredyRat, an open-source custom Python tool that analyzes Noldus Ethovision-generated raw data files to identify Darters and quantify both conditioned and unconditioned responses. We find that like freezing, conditioned darting occurrences scale with experimental alterations. While most darting occurs in females, we find that with an extended training protocol, darting can emerge in males as well. Collectively, our data suggest that darting reflects a behavioral switch in conditioned responding that is a product of both an individual animals sex, shock reactivity, and experimental parameters, underscoring the need for careful consideration of sex as a biological variable in classic learning paradigms. Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships BackgroundSmall nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions.

ResultsWe used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver and brain). We identified 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. 59% of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, as opposed to only 16% of the correlated non-coding host gene/snoRNA pairs.

ConclusionsOur results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues. Biomechanical property of limbal niche maintains stemness through YAP Stem cells (SCs) decision to self-renew or differentiate largely depends on the external control of their niche. However, the complex mechanisms that underlie this crosstalk are poorly understood. To address this question, we focused on the corneal epithelial SC model in which the SC niche, known as the limbus, is spatially segregated from the differentiation compartment. We report that the unique biomechanical property of the limbus supports the nuclear localization and function of Yes-associated protein (YAP), a putative mediator of the mechanotransduction pathway. Perturbation of tissue stiffness or YAP activity affects SC function as well as tissue integrity under homeostasis and significantly inhibited the regeneration of the SC population following SC depletion. In vitro experiments revealed that substrates with the rigidity of the corneal differentiation compartment inhibit YAP localization and induce differentiation, a mechanism that is mediated by the TGFbeta-SMAD2/3 pathway. Taken together, these results indicate that SC sense biomechanical niche signals and that manipulation of mechano-sensory machinery or its downstream biochemical output may bear fruits in SC expansion for regenerative therapy. In vitro evolution of uracil glycosylase towards DnaKJ and GroEL binding evolves different misfolded states Natural evolution is driven by random mutations that improve fitness. In vitro evolution mimics this process, however, on a short time-scale and is driven by the given bait. Here, we used directed in vitro evolution of a random library of Uracil glycosylase (eUNG) displayed on yeast surface to select for binding to chaperones GroEL, DnaK+DnaJ+ATP (DnaKJ) or E.coli cell extract (CE). Using binding to the eUNG inhibitor Ugi as probe for native foldedess, the CE selected population was further divided to Ugi binders (+U) (native) or non-binders (-U). We found that GroEL, DnaKJ and CE-U select and enrich for mutations causing eUNG to misfold, with the three being enriched in mutations in buried and conserved positions, with a tendency to increase positive charge. Still, each selection, as well as CE+U and natural evolution of eUNG has its own trajectory. While GroEL and CE-U selected for mutants highly sensitive to protease cleavage, DnaKJ selected for partially structured misfolded species with a tendency to refold, making them less sensitive to proteases. CE+U selected for more neutral mutations than natural evolution. In a more general context, our results show that GroEL has a higher tendency to purge promiscuous misfolded protein mutants from the system, while DnaKJ binds mutants misfolding-prone species that are, upon chaperone release, more likely to natively refold. CE-U shares some of the properties of GroEL and DnaKJ selected populations, while harboring also unique properties, explained by the existence of additional chaperones in CE, such as Tig, HtpG and ClpB. SARS-CoV-2 RdRp uses NDPs as a substrate and is able to incorporate NHC into RNA from diphosphate form molnupiravir The coronavirus disease 2019 (COVID-19) has been ravaging throughout the world for more than two years and has severely impaired both human health and the economy. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) employs the viral RNA-dependent RNA polymerase (RdRp) complex for genome replication and transcription, making RdRp an appealing target for antiviral drug development. Here, we reveal that RdRp can recognize and utilize nucleoside diphosphates (NDPs) as a substrate to synthesize RNAs with an efficiency of about two thirds of using nucleoside triphosphates (NTPs) as a substrate. NDPs incorporation is also template-specific and has high fidelity. Moreover, RdRp can incorporate {beta}-d-N4-hydroxycytidine (NHC) into RNA while using diphosphate form molnupiravir (MDP) as a substrate. We also observed that MDP is a better substrate for RdRp than the triphosphate form molnupiravir (MTP). Cargo-mediated mechanisms reduce inter-motor mechanical interference, promote load-sharing and enhance processivity in teams of molecular motors In cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of cytoskeletal filaments. How motors that typically mechanically interfere with each other, work as teams is unclear. Here we explored the possibility that purely physical mechanisms may potentially enhance teamwork, both at the single motor and cargo level. To explore these mechanisms, we developed a 3D dynamical simulation of cargo transport along microtubules by teams of canonically non-cooperative kinesin-1 motors. We accounted for cargo membrane fluidity by explicitly simulating the Brownian dynamics of motors on the cargo surface and considered both the load and ATP dependence of single motor functioning. We showed explicitly, for the first time, that surface fluidity leads to the reduction of negative mechanical interference between kinesins, enhancing load sharing thereby decreasing single motor off-rates and increasing processivity. Remarkably, we also showed that, independent of fluidity, increasing numbers of bound motors pull the cargo closer to the microtubule, increasing the on-rates of individual unbound motors, resulting in a cooperative increase in bound motor numbers that depends on 3D cargo geometry. At the cargo level, surface fluidity makes more motors available for binding, though this effect is significant only at low ATP or high motor density. Interestingly, we find that the fluidity induced reduction in mechanical interference dominates over the increased availability of motors for typical physiological and in vitro conditions, this allowing us to reconcile different experimental results in different regimes. Finally, we show that these effects can altogether result in enhanced mechanical efficiency and tunable cargo run-lengths for teams of molecular motors over physiological ranges of fluidity with implications for new experimental validation efforts, transport in vivo, artificial cargo design and multi-motor-driven mechanical processes in general.

Author summaryIn cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of protein filaments. How do intrinsically non-cooperative motors function as teams within cells? In this paper, we show, using computer simulations, that the fluid surfaces of cellular cargo reduce the mechanical interference between motors allowing better load sharing and decreasing their detachment rates, thereby increasing the distance over which they can carry cargo. We additionally found that motors pull cargo closer to the filament increasing the attachment rates of other unbound motors. These effects act synergistically with an increased availability of motors due to fluidity to further increase travel distances. Our simulation model accounted for the dynamics of the motors on the cargo surface and their load and ATP dependent kinetics, allowing us to connect single motor properties to overall transport. Our work on understanding how teamwork arises in mechanically coupled motors sheds new light on cellular processes, reconciles existing observations, encourages new experimental validation efforts and can also suggest new ways of improving mechanical efficiency and transport of artificial cargo powered by motor teams. Trehalose increases tomato drought tolerance, induces defenses, and increases resistance to bacterial wilt disease Ralstonia solanacearum causes bacterial wilt disease, leading to severe crop losses. Xylem sap from R. solanacearum-infected tomato is enriched in the disaccharide trehalose. Water-stressed plants also accumulate trehalose, which increases drought tolerance via abscisic acid (ABA) signaling. Because R. solanacearum-infected plants suffer reduced water flow, we hypothesized that bacterial wilt physiologically mimics drought stress, which trehalose could mitigate. We found that R. solanacearum-infected plants differentially expressed drought-associated genes, including those involved in ABA and trehalose metabolism, and had more ABA in xylem sap. Consistent with this, treating tomato roots with ABA reduced both stomatal conductance and stem colonization by R. solanacearum. Treating roots with trehalose increased xylem sap ABA and reduced plant water use by lowering stomatal conductance and temporarily improving water use efficiency. Trehalose treatment also upregulated expression of salicylic acid (SA)-dependent tomato defense genes; increased xylem sap levels of SA and other antimicrobial compounds; and increased bacterial wilt resistance of SA-insensitive NahG tomato plants. Additionally, trehalose treatment increased xylem concentrations of jasmonic acid and related oxylipins. Finally, trehalose-treated plants were substantially more resistant to bacterial wilt disease. Together, these data show that exogenous trehalose reduced both water stress and bacterial wilt disease and triggered systemic disease resistance, possibly through a Damage Associated Molecular Pattern (DAMP) response pathway. This suite of responses revealed unexpected linkages between plant responses to biotic and abiotic stress and suggested that R. solanacearum-infected plants increase trehalose to improve water use efficiency and increase wilt disease resistance. The pathogen may degrade trehalose to counter these efforts. Together, these results suggest that treating tomatoes with exogenous trehalose could be a practical strategy for bacterial wilt management. Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data. Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli (E. coli) and published experimental data. "Adopt a Microorganism" methodology enhances the discourse richness of high school students in both hybrid learning and remote education The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Second Heart Field-derived Cells Contribute to Angiotensin II-mediated Ascending Aortopathies BackgroundThe ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies.

MethodsAscending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry assisted proteomics, and molecular features of SHF-derived cells were determined by single cell transcriptomic analyses. Genetic deletion of either low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-{beta} receptor 2 (Tgfbr2) in SHF- derived cells was conducted to examine the impact of SHF-derived cells on vascular integrity.

ResultsPathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas following AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion, prior to overt pathology, evoked downregulation of SMC proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single cell transcriptomics results identified plasminogen activator inhibitor 1 (PAI1) as the most increased protein in SHF-derived SMCs and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies.

ConclusionSHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and TGF-{beta} signaling associated with increases of aortic PAI1.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/930917v6_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@185e3d9org.highwire.dtl.DTLVardef@131d702org.highwire.dtl.DTLVardef@11afa42org.highwire.dtl.DTLVardef@242786_HPS_FORMAT_FIGEXP  M_FIG C_FIG Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABS- SHF-derived SMCs and fibroblasts associate with AngII-induced aortic pathologies.
- AngII induces a distinct fibroblast sub-cluster that is less abundant for mRNAs related to major extracellular components and TGF{beta} ligands and receptors, but more abundant for proliferative genes.
- TGFBR2 deletion in SHF-derived cells are embryonic lethal with significant dilatation of the outflow tract in mice.
- SHF-specific deletion of LRP1 leads to aortic pathologies in mice, supporting the importance of SHF-derived cells in maintaining ascending aortic wall integrity.


What are the clinical implications?- Heterogeneity of the embryonic origins of SMCs and fibroblasts contributes to complex mechanisms of vasculopathy formation, which should be considered when investigating the pathogenesis of thoracic aortopathies. An exploratory study on the role of the stiffness of breast cancer cells in their detachment from spheroids and migration in 3D collagen matrices BackgroundTumour-cell detachment is a critical early event in the metastatic cascade. However, the role of the cells mechanical properties in detachment and migration is not well understood. This exploratory study aimed to assess how intracellular stiffness changes these processes.

MethodsMDA-MB-231 cells were embedded as 10,000-cell spheroids in 2 and 4 mg/ml collagen matrices. Intracellular stiffness was assessed with mitochondria tracking microrheology of cells that migrated distances equivalent to four and six times the cell diameter (dC) from the spheroid and compared to cells at the spheroid surface (0dC), representing medium, high and no migration, respectively.

Results and discussionThe mitochondrial mean square displacement and intracellular stiffness decreased during detachment and migration for both collagen concentrations (i.e. rigidities). The mean square displacement of 4dC and 6dC cells was similar, whereas cell stiffness was lower for 4dC than for 6dC cells. With increasing matrix rigidity, the intracellular stiffness decreased for 0dC cells and did not change for 4dC and 6dC cells. It is proposed that decreased cell stiffness drives detachment and migration and increased matrix rigidity physically hinders migration, and cells need to become softer or remodel the environment to migrate. The independence of the stiffness of migrated cells from matrix rigidity suggests that cells remodel their environment through matrix proteins cleavage to migrate.

ConclusionsThe study revealed the collective effects of enhanced migratory conditions and increased matrix rigidity on the mechanical properties of the cells. The expression of matrix metalloproteinases and transforming growth factor {beta} and the role of cell volume on detachment and migration in matrices with varying pore sizes are proposed targets for further studies on metastatic cancer cells. H3K36 methylation and DNA-binding both promote Ioc4 recruitment and Isw1b remodeller function The Isw1b chromatin-remodelling complex is specifically recruited to gene bodies to help retain pre-existing histones during transcription by RNA polymerase II. Recruitment is dependent on H3K36 methylation and the Isw1b subunit Ioc4, which contains an N-terminal PWWP domain. Here, we present the crystal structure of the Ioc4-PWWP domain, including a detailed functional characterization of the domain on its own as well as in the context of full-length Ioc4 and the Isw1b remodeller. The Ioc4-PWWP domain preferentially binds H3K36me3-containing nucleosomes. Its ability to bind DNA is required for nucleosome binding. It is also furthered by the unique insertion motif present in Ioc4-PWWP. The ability to bind H3K36me3 and DNA promote the interaction of full-length Ioc4 with nucleosomes in vitro and they are necessary for its recruitment to gene bodies in vivo. Furthermore, a fully functional Ioc4-PWWP domain promotes efficient remodelling by Isw1b and the maintenance of ordered chromatin in vivo, thereby preventing the production of non-coding RNAs. Bulk-assembly of monodisperse coacervates and giant unilamellar vesicles with programmable hierarchical complexity Compartmentalization is an essential step for the emergence of protocellular life on the early earth and the endeavor to bottom-up construct synthetic cells in the lab. Among manifold natural strategies for compartmentalization, assembly of lipid vesicles or coacervate droplets with resemblance to cell envelope or cytoplasm have emerged as two dominant paradigms. However, the spontaneous assembly of lipid vesicles or coacervates generally results in polydisperse microcompartments and lacks the ability to efficiently integrate functional building blocks towards defined complexity, which give rise to the difficulty to achieve the order and complexity towards the scope of that of life via spontaneous assembly. Herein, we show that the interplay of coacervates and colloidal particles provides a bulk-assembly approach to form monodisperse coacervates and giant unilamellar vesicles (GUVs) with programmable hierarchical complexity. The hierarchical complexity of the synthetic cell microcompartments can be delicately engineered from the control of the spatial or temporal organization of components in entity unit to manifold forms of interconnected synthetic cell consortia, achieving a compartment hierarchy analogous to the organelle-cell-tissue structure. The increase in complexity gives rise to emergent properties, for instance, collective morphology evolution of coacervate assemblages, gated permeability of GUVs without sophisticated protein machinery, and remarkable structural and functional stability of GUVs at extreme conditions. This work paves an unprecedented step to form monodisperse, hierarchical coacervates and GUVs via bulk-assembly, which provides a prebiotically plausible approach for the proper integration of inanimate matter towards the order and complexity of life and monodisperse, hierarchical microdroplets for follow-up scientific and technological applications. Bioactive constituents of Verbena officinalis regulate killing efficiency of primary human natural killer cells by accelerating killing processes BackgroundNatural killer (NK) cells play a key role in eliminating tumorigenic and pathogen-infected cells. Verbena officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine, exhibiting anti-tumor and anti-inflammation activity, but its role in NK cells remains unclear.

PurposeThe impact of bioactive constituents of V. officinalis on immune responses remains largely elusive. In this work we investigated the potential targets of V. officinalis and focused on killing efficiency and related functions of NK cells regulated by bioactive constituents of V. officinalis.

Study design/methodsWe used primary human NK cells from peripheral blood mononuclear cells. Potential regulatory roles of selected compounds in NK killing function-related genes were first analyzed by network pharmacology approaches. Potential engagement between compounds and NK receptors was examined by molecular docking assay. Killing efficiency of NK cells was determined with real-time killing assay and live-cell imaging. Proliferation was examined by CFSE staining. Expression of cytotoxic proteins was analyzed using flow cytometry. Lytic granule release was quantified by CD107a degranulation assay. Contact time required for killing and determination of serial killers were analyzed using live cell imaging results.

ResultsResults from network pharmacology approaches and molecular docking analyses predicted that the five bioactive compounds (acteoside, apigenin, kaempferol, verbenalin and hastatoside) from V. officinalis can regulated various key genes essential for NK effector functions and can bind to NK inhibitory receptors as well as activating receptors, indicating their potential role in regulating NK killing capacity. Analyses of NK killing efficiency revealed that out of these five compounds verbenalin exhibited an encouraging potency to enhance NK killing efficiency. Further investigation showed that verbenalin did not affect proliferation, expression of cytotoxic proteins, or lytic granule degranulation, but rather reduced contact time required for killing, enhanced total killing events per NK cell, and elevated the fraction of killing competent NK cells.

ConclusionsIn this work, we have identified verbenalin as the most potent bioactive constituent from V. officinalis to enhance NK cell killing efficiency via accelerating killing processes and converting non-killers to killing competent NK cells without affecting the lytic granule pathway. Untangling the complexity of priority effects in multispecies communities The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this frame-work, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles, and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of history-dependent community assembly. Estimating the rate of plasmid transfer with an adapted Luria-Delbrück fluctuation analysis To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need a reliable estimate of their rate of transfer between bacterial cells. However, accurate estimates of plasmid transfer have remained elusive due to biological and experimental complexity. Current methods to measure transfer rate can be confounded by many factors. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. Inspired by the classic fluctuation analysis of Luria and Delbruck, we develop a novel approach, the Luria-Delbruck method ( LDM), for estimating plasmid transfer rate. Our new approach embraces the stochasticity of conjugation departing from the current deterministic population dynamic methods. In addition, the LDM overcomes obstacles of traditional methods by not being affected by different growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude.

Significance StatementConjugative plasmids play significant roles in the ecology and evolution of microbial communities. Notably, antibiotic resistance genes are often encoded on conjugative plasmids. Thus, conjugation--the transfer of a plasmid copy from one cell to another--is a common way for antibiotic resistance to spread between important clinical pathogens. For both public health modeling and a basic understanding of microbial population biology, accurate estimates of this fundamental rate are of great consequence. We show that widely used methods can lead to biased estimates, deviating from true values by several orders of magnitude. Therefore, we developed a new approach, inspired by the classic fluctuation analysis of Luria and Delbruck, for accurately assessing the rate of plasmid conjugation under a variety of conditions.