A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions AO_SCPLOWBSTRACTC_SCPLOWDrug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (AUC = 0.83 for synergy, AUC = 0.98 for antagonism) in predicting drug interactions for E. coli cultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population-FBA identified two sub-populations of E. coli cells defined by regulation of cis- to trans-isomerization of unsaturated fatty acids with distinct effects on drug interactions. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use.

SO_SCPLOWIGNIFICANCEC_SCPLOWWorldwide, 700,000 people die each year from drug-resistant infections. Drug combinations have great potential to reduce the spread of drug-resistant bacteria. However, their potency is impacted by both the pathogen growth environment and the heterogeneity in pathogen metabolism. The metabolic heterogeneity in a pathogen population allows them to survive antibiotic treatment. Here we present a flexible machine-learning framework that utilizes diverse data types to effectively search through the large design space of both sequential and simultaneous combination therapies across hundreds of simulated growth conditions and pathogen metabolic states. Our approach can serve as a useful guide for the selection of robustly synergistic drug combinations.
Predicting microbiome compositions from species assemblages through deep learning. Microbes can form complex communities that perform critical functions in maintaining the integrity of their environment or their hosts well-being. Rationally managing these microbial communities requires improving our ability to predict how different species assemblages affect the final species composition of the community. However, making such a prediction remains challenging because of our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. To overcome this challenge, here we present a deep learning framework that automatically learns the map between species assemblages and community compositions from training data only, without knowledge of any of the above processes. First, we systematically validate our framework using synthetic data generated by classical population dynamics models. Then, we apply it to experimental data of both in vitro and in vivo communities, including ocean and soil microbial communities, Drosophila melanogaster gut microbiota, and human gut and oral microbiota. In particular, we show how our framework learns to perform accurate out-of-sample predictions of complex community compositions from a small number of training samples. Our results demonstrate how deep learning can enable us to understand better and potentially manage complex microbial communities.
Co-infection of Candidatus Piscichlamydia trichopodus (order Chlamydiales) and Henneguya sp (Myxosporea, Myxobolidae) in snakeskin gourami Trichopodus pectoralis (Regan 1910) The present study describes a simultaneous infection of a novel Chlamydia-like organism (CLO) with a Myxozoa parasite, Henneguya sp. in snakeskin gourami Trichopodus pectoralis in Thailand. A new CLO is proposed "Candidatus Piscichlamydia trichopodus" (CPT) based on 16S rRNA phylogenetic analysis. Systemic intracellular CPT infection was confirmed by histological examination, in situ hybridization, PCR assay, and sequencing of 16S rRNA. This novel pathogen belongs to the order Chlamydiales but differs in certain aspects from other species. The histopathological changes associated with CPT infection were different from the typical pathological lesions of epitheliocystis caused by previously known CLO. Unlike other CLO, CPT localized in the connective tissue rather than in the epithelial cells and formed smaller clumps of intracellular bacteria that stained dark blue with hematoxylin. On the other hand, typical myxospores of the genus Henneguya with tails were observed in the gill sections. Infection with Henneguya sp. resulted in extensive destruction of the gill filaments, most likely leading to respiratory distress. Due to the frequency of co-infections and the unavailability of culture methods for CLO and Henneguya sp, it was difficult to determine which pathogens were directly responsible for the associated mortality. However, co-infections may increase the negative impact on the host and the severity of the disease. Given the commercial importance of the snakeskin gourami and its significant aquaculture potential, the findings of this study are important for further studies on disease prevention. Psychedelics flatten the brain's energy landscape: evidence from receptor-informed network control theory Psychedelics like lysergic acid diethylamide (LSD) and psilocybin offer a powerful window into the function of the human brain and mind, by temporarily altering subjective experience through their neurochemical effects. A recent model postulates that serotonin 2a (5-HT2a) receptor agonism allows the brain to explore its dynamic landscape more readily, as reflected by more diverse (entropic) brain activity. We postulate that this increase in entropy may arise in part from a flattening of the brains control energy landscape, which can be observed using network control theory to quantify the energy required to transition between recurrent brain states measured using functional magnetic resonance imaging (fMRI) in individuals under LSD, psilocybin, and placebo conditions. We show that LSD and psilocybin reduce the amount of control energy required for brain state transitions, and, furthermore, that, across individuals, LSDs reduction in control energy correlates with more frequent state transitions and increased entropy of brain state dynamics. Through network control analysis that incorporates the spatial distribution of 5-HT2a receptors from publicly available (non-drug) positron emission tomography (PET) maps, we demonstrate the specific role of this receptor in reducing control energy. Our findings provide evidence that 5-HT2a receptor agonist compounds allow for more facile state transitions and more temporally diverse brain activity. More broadly, by combining receptor-informed network control theory with pharmacological modulation, our work highlights the potential of this approach in studying the impacts of targeted neuropharmacological manipulation on brain activity dynamics.

Significance StatementWe present a multi-modal framework for quantifying the effects of two psychedelic drugs (LSD and psilocybin) on brain dynamics by combining functional magnetic resonance imaging (fMRI), diffusion MRI (dMRI), positron emission tomography (PET) and network control theory. Our findings provide evidence that psychedelics flatten the brains control energy landscape, allowing for more facile state transitions and more temporally diverse brain activity. We also demonstrate that the spatial distribution of serotonin 2a receptors - the main target of LSD and psilocybin - is optimized for generating these effects. This approach could be used to understand how drugs act on different receptors in the brain to influence brain activity dynamics. Metacommunity dynamics and the detection of species associations in co-occurrence analyses: why patch disturbance matters O_LI1: Many statistical methods attempt to detect species associations - and so infer inter-specific interactions - from species co-occurrence patterns. Habitat heterogeneity and out-of-equilibrium colonization histories are well recognized as potentially causing species associations, even when interactions are absent. The potential for patch disturbance, a classical component of metacommunity dynamics, to also drive spurious species associations has however been over-looked.
C_LIO_LI2: Using a new general metacommunity model, we derive mathematical predictions regarding how patch disturbance would affect the patterns of species associations detected in "null" co-occurrence matrices. We also conduct numerical simulations to test our predictions and to compare the performance of several widespread statistical methods, including direct tests of pairwise independence, matrix permutation approaches and joint species distribution modelling.
C_LIO_LI3: We show how classical metacommunity dynamics can produce statistical associations, both positive and negative, even when species do not interact, when there is no habitat heterogeneity, and at equilibrium. This occurs as soon as there is some rate of patch disturbance (i.e. simultaneous extinction of several species in a patch) and/or a finite life-span of patches, a common feature of a broad range of plant, animal or microbial systems.
C_LIO_LI4: Patch disturbance can compromise species co-occurrence analyses and cause the artefactual detection of species associations if not taken into account. Including patch age (i.e. the time since the last patch disturbance event) as a covariate in a joint species distribution model can resolve the artefact. However, this requires additional data that often are not available in practice. We argue that the consequences of patch disturbance should not be underestimated when analysing species distribution patterns in metacommunity-like systems.
C_LI Structure-Functional-Selectivity Relationship Studies on A-86929 Analogs and Small biaryl Fragments toward Discovery of biased D1 agonists Dopamine regulates normal functions such as movement, reinforcement learning, and cognition, and its dysfunction has been implicated in multiple psychiatric and neurological disorders. Dopamine acts through the D1- (D1R and D5R) and D2-class (D2R, D3R and D4R) of seven transmembrane receptors, and activates both G-protein- and {beta}-arrestin-dependent signaling pathways, to mediate its physiological effects. Current dopamine receptor-based therapies are used to ameliorate motor deficits in Parkinsons disease, or as antipsychotic medications for schizophrenia. These drugs show efficacy for ameliorating only some symptoms caused by dopamine dysfunction and are plagued by debilitating side-effects. Studies in primates and rodents have shown that shifting the balance of dopamine receptor signaling towards the arrestin pathway can be beneficial for inducing normal movement, while reducing motor side-effects such as dyskinesias, and can be efficacious at enhancing cognitive function compared to balanced agonists. Several structure-activity-relationship (SAR) studies have embarked on discovering {beta}-arrestin-biased dopamine agonists, focused on D2 partial agonists, non-catechol D1 agonists, and mixed D1/D2R dopamine receptor agonists. Here, we describe an SAR study to identify novel D1R {beta}-arrestin biased ligands using A-86929, a high-affinity D1R catechol agonist, as a core scaffold. Previously described and novel analogs of A-86929 were synthesized and screened in vitro for structure-functional-selectivity relationships (SFSR) studies to identify chemical motifs responsible for {beta}-arrestin biased activity at both D1 and D2Rs. Most of the A-86929 analogs screened were G protein biased but none of them were exclusively arrestin-biased. Additionally, various catechol aryl fragments were designed and synthesized. Other compounds surveyed included hydroxyl and chloro analogs of dopamine to test for hydrogen bonding and ionic interactions. Some of these small molecular probes displayed weak bias towards the {beta}-arrestin pathway. Continued in-depth SFSR studies informed by structure determination, molecular modeling, and mutagenesis studies will facilitate discovery of potent and efficacious arrestin-biased dopamine receptor ligands. Population differences in the length and early-life dynamics of telomeres among European pied flycatchers Telomere length and shortening rate are increasingly used as biomarkers for long-term costs in ecological and evolutionary studies because of their relationships with survival and fitness. Both early-life conditions and growth, and later-life stressors can create variation in telomere shortening rate. Studies on between- population telomere length and dynamics are scarce, despite the expectation that populations exposed to varying environmental constraints would present divergent telomere length patterns. The pied flycatcher (Ficedula hypoleuca) is a passerine bird breeding across Eurasia (from Spain to western Siberia) and migrating through the Iberian Peninsula to spend the non-breeding period in sub-Saharan Africa. Thus, different populations show marked differences in migration distance. We studied the large-scale variation of telomere length and early-life dynamics in the pied flycatcher by comparing six European populations across a north- south gradient (Finland, Estonia, England, and Spain) predicting negative effect of migration distance on adult telomere length, and of nestling growth on nestling telomere dynamics. There were clear population differences in telomere length, with English birds from mid-latitudes having the longest telomeres. Telomere length did not thus show consistent latitudinal variation and was not linearly linked to differences in migration distance. Early-life telomere shortening rate tended to vary between populations. Fast growth was associated with shorter telomeres in the early life, but faster nestling growth affected telomeres more negatively in northern than southern populations. While the sources of between-population differences in telomere-related biology remain to be more intensively studied, our study illustrates the need to expand telomere studies at the between-population level. Design, immunogenicity and efficacy of a Pan-SARS-CoV-2 synthetic DNA vaccine Here we have employed SynCon(R) design technology to construct a DNA vaccine expressing a pan-Spike immunogen (INO-4802) to induce broad immunity across SARS-CoV-2 variants of concern (VOC). Compared to WT and VOC-matched vaccines which showed reduced cross-neutralizing activity, INO-4802 induced potent neutralizing antibodies and T cell responses against WT as well as B.1.1.7, P.1, and B.1.351 VOCs in a murine model. In addition, a hamster challenge model demonstrated that INO-4802 conferred superior protection following intranasal B.1.351 challenge. Protection against weight loss associated with WT, B.1.1.7, P.1 and B.1.617.2 challenge was also demonstrated. Vaccinated hamsters showed enhanced humoral responses against VOC in a heterologous WT vaccine prime and INO-4802 boost setting. These results demonstrate the potential of the pan-SARS-CoV-2 vaccine, INO-4802 to induce cross-reactive immune responses against emerging VOC as either a standalone vaccine, or as a potential boost for individuals previously immunized with WT-matched vaccines. Behavioral and postural analyses establish sleep-like states for mosquitoes that can impact host landing and blood feeding Sleep is an evolutionarily conserved process that has been described in different animal systems. For insects, sleep characterization has been primarily achieved using behavioral and electrophysiological correlates in a few systems. Sleep in mosquitoes, which are important vectors of disease-causing pathogens, has not been directly examined. This is surprising as circadian rhythms, which have been well studied in mosquitoes, influence sleep in other systems. In this study, we characterized sleep in mosquitoes using body posture analysis and behavioral correlates, and quantified the effect of sleep deprivation on sleep rebound, host landing and blood-feeding propensity. Body and appendage position metrics revealed a clear distinction between the posture of mosquitoes in their putative sleep and awake states for multiple species, which correlate with a reduction in responsiveness to host cues. Sleep assessment informed by these posture analyses indicated significantly more sleep during periods of low activity. Nighttime and daytime sleep deprivation resulting from the delivery of vibration stimuli induced sleep rebound in the subsequent phase in day and night active mosquitoes, respectively. Lastly, sleep deprivation suppressed host landing in both laboratory and field settings and also impaired blood feeding of a human host when mosquitoes would normally be active. These results suggest that quantifiable sleep states occur in mosquitoes, and highlight the potential epidemiological importance of mosquito sleep. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology 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. Exploitation of the genetic variability in the genotype of Egyptian Wheat by studding Molecular Markers, Molecular Docking and Nano Composites. Regulation of leaf and stem rust This manuscript has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. Building a Knowledge Graph to Enable Precision Medicine Developing personalized diagnostic strategies and targeted treatments requires a deep understanding of disease biology and the ability to dissect the relationship between molecular and genetic factors and their phenotypic consequences. However, such knowledge is fragmented across publications, non-standardized research repositories, and evolving ontologies describing various scales of biological organization between genotypes and clinical phenotypes. Here, we present PrimeKG, a precision medicine-oriented knowledge graph that provides a holistic view of diseases. PrimeKG integrates 20 high-quality resources to describe 17,080 diseases with 4,050,249 relationships representing ten major biological scales, including disease-associated protein perturbations, biological processes and pathways, anatomical and phenotypic scales, and the entire range of approved and experimental drugs with their therapeutic action, considerably expanding previous efforts in disease-rooted knowledge graphs. In addition, PrimeKG supports artificial intelligence analyses of how drugs might target disease-associated molecular perturbations by containing an abundance of 'indications', 'contradictions', and 'off-label use' drug-disease edges lacking in other knowledge graphs. We accompany PrimeKG's graph structure with text descriptions of clinical guidelines to enable multimodal analyses. Hypoxia reduces cell attachment of SARS-CoV-2 spike protein by modulating the expression of ACE2, neuropilin-1, syndecan-1 and cellular heparan sulfate A main clinical parameter of COVID-19 pathophysiology is hypoxia. Here we show that hypoxia decreases the attachment of the receptor binding domain (RBD) and the S1 subunit (S1) of the spike protein of SARS-CoV-2 to epithelial cells. In Vero E6 cells, hypoxia reduces the protein levels of ACE2 and neuropilin-1 (NRP1), which might in part explain the observed reduction of the infection rate. In addition, hypoxia inhibits the binding of the spike to NCI-H460 human lung epithelial cells by decreasing the cell surface levels of heparan sulfate (HS), a known attachment receptor of SARS-CoV-2. This interaction is also reduced by lactoferrin, a glycoprotein that blocks HS moieties on the cell surface. The expression of syndecan-1, an HS-containing proteoglycan expressed in lung, is inhibited by hypoxia on a HIF-1-dependent manner. Hypoxia or deletion of syndecan-1 results in reduced binding of the RBD to host cells. Our study indicates that hypoxia acts to prevent SARS-CoV-2 infection, suggesting that the hypoxia signaling pathway might offer therapeutic opportunities for the treatment of COVID-19. 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. HIGHER VIRAL VIRULENCE SELECTS FOR FASTER EVOLUTION OF HOST RESISTANCE Parasites and pathogens vary strikingly in their virulence and the resulting selection they impose on their hosts. While the evolution of different virulence levels is well studied, the evolution of host resistance in response to different virulence levels is less understood and as of now mainly based on observations and theoretical predictions with few experimental tests. Increased virulence can increase selection for host resistance evolution if resistance costs are outweighed by the benefits of avoiding infection. To test this, we experimentally evolved the bacterium Vibrio alginolyticus in the presence of two variants of the filamentous phage, VALG{Phi}8, that differ in their virulence. The bacterial host exhibited two alternative defence strategies against future phage infection: (1) super infection exclusion (SIE) whereby phage-infected cells were immune to subsequent infection at a cost of reduced growth, and (2) surface receptor mutations (SRM) in genes encoding the MSHA type-IV pilus providing resistance to infection by preventing phage attachment. While SIE emerged rapidly against both phages, SRM evolved faster against the high virulence compared to the low virulence phage. Using a mathematical model of our system we show that increasing virulence strengthens selection for SRM due to the higher costs of infection suffered by SIE immune hosts. In both the experiments and the model, higher levels of SRM in the host population drove more rapid phage extinction. Thus, by accelerating the evolution of host resistance, more virulent phages caused shorter epidemics. Relationship between shear wave velocity and muscle activation is inconsistent across different muscle types There is an increasing use of shear wave ultrasound elastography to quantify mechanical properties of muscles under various conditions such as changes muscle length and levels of activation in healthy and pathological muscle. However, little is known about the variability in shear wave velocity among muscles as most studies investigate one specific muscle. The purpose of this study was to determine if the relationship between SWV and muscle activation is consistent across muscles with different architectures: biceps brachii, tibialis anterior, and medial gastrocnemius, All measures were made at matching levels of activation and approximately at the optimal length for each muscle to control for length-dependent changes in the relationship between activation and force or stiffness. We also conducted a control experiment to determine how the passive force within a muscle alters the relationship between muscle activation and shear wave velocity. The relationship between shear wave velocity-squared and activation above 10% MVC differed across muscles, with biceps brachii and medial gastrocnemius showing a lower slope than tibialis anterior. Shear wave velocity-squared also differed between muscles at the shortest length (p<0.001) and the increase in shear wave velocity-squared with muscle lengthening also differed between muscle types (p = 0.005) Muscle-specific differences could not be explained by the architectural features such as pennation angle, fiber length, and physiological cross-sectional area. Our results demonstrate that there is not a unique relationship between muscle activation and shear wave velocity, highlighting the importance of understanding the many factors contributing to shear wave propagation in muscle before elastography can be used to make quantitative comparisons across muscle types. Patterned apoptosis has an instructive role for local growth and tissue shape in a fast-growing epithelium What regulates organ size and shape remains one of the fundamental mysteries of modern biology. So far, research in this area has primarily focused on deciphering the regulation in time and space of growth and cell division, while the contribution of cell death has been much more neglected. This includes studies of the Drosophila wing imaginal disc, the prospective fly wing which undergoes massive growth during larval stage, and represents one of the best characterised systems for the study of growth and patterning. So far, it has been assumed that cell death was relatively neglectable in this tissue and as a result the pattern of growth was usually attributed to the distribution of cell division. Here, using systematic mapping and registration combined with quantitative assessment of clone size and disappearance, we show for the first time that cell death is not neglectable, and outline a persistent pattern of cell death and clone elimination in the disc. Local variation of cell death is associated with local variation of clone size, pointing to an impact of cell death on local growth which is not fully compensated by proliferation. Using morphometric analyses of adult wing shape and genetic perturbations, we provide evidence that patterned death affects locally and globally adult wing shape and size. This study describes a roadmap for accurate assessment of the contribution of cell death to tissue shape, and outlines for the first time an important instructive role of cell death in modulating quantitatively local growth and the morphogenesis of a fast-growing tissue. PRSS2 stimulates tumor growth by remodeling the TME via repression of Tsp1 In the earliest stages of tumor development, epithelial tumors (carcinomas) are physically confined to the area of the tissue in which they form. These nascent lesions (carcinomas in situ) are sequestered from the tissue parenchyma by the basement membrane. Within the tissue parenchyma lie a myriad of cell types comprised of fibroblasts, immune and inflammatory cells and endothelial cells. Upon invasion across the basement membrane and into the tissue parenchyma, tumors must manipulate the expression of pro- and anti-tumorigenic proteins such that pro-tumorigenic factors are produced in excess to anti-tumorigenic proteins. One such anti-tumorigenic protein is Thrombospondin-1 (Tsp-1). We have previously demonstrated that stimulation of Tsp-1 in the tumor microenvironment (TME) potently inhibits tumor growth and progression and in some cases induces tumor regression. Here, we identify a novel tumor-mediated mechanism to repress the expression of Tsp-1 in the TME via secretion of the serine protease PRSS2. We demonstrate that PRSS2 represses Tsp-1, not via its enzymatic activity, but by binding to low-density lipoprotein receptor-related protein 1 (LRP1). These findings describe a novel activity for PRSS2 through binding to LRP1 and represent a potential therapeutic strategy to treat cancer by blocking the PRSS2-mediated repression of Tsp-1. Recognition of discrete export signals in flagellar subunits during bacterial Type III secretion Type III Secretion Systems (T3SS) deliver subunits from the bacterial cytosol to nascent cell surface flagella. Early flagellar subunits that form the rod and hook substructures are unchaperoned and contain their own export signals. A gate recognition motif (GRM) docks them at the FlhBc component of the FlhAB-FliPQR export gate, but the gate must then be opened and subunits must be unfolded to pass through the flagellar channel. This induced us to seek further signals on the subunits. Here, we identify a second signal at the extreme N-terminus of flagellar rod and hook subunits and determine that key to the signal is its hydrophobicity. We show that the two export signal elements are recognised separately and sequentially, as the N-terminal signal is recognised by the flagellar export machinery only after subunits have docked at FlhBC via the GRM. The position of the N-terminal hydrophobic signal in the subunit sequence relative to the GRM appeared to be important, as a FlgD deletion variant (FlgDshort), in which the distance between the N-terminal signal and the GRM was shortened,  stalled at the export machinery and was not exported. The attenuation of motility caused by FlgDshort was suppressed by mutations that destabilised the closed conformation of the FlhAB-FliPQR export gate, suggesting that the hydrophobic N-terminal signal might trigger opening of the flagellar export gate. A multiscale lipid and cellular atlas of the human kidney The human kidney is composed of over 26 cell types that actively coordinate with each other to form higher-order structures, such as the nephron. It is not yet understood how these structures vary throughout a single organ or amongst the same organs within the human population. We have developed an extensive lipid and cellular atlas of the human kidney consisting of over 3 million cells comprising 75,000 functional tissue units (i.e., glomeruli, proximal tubules, distal tubules, and collecting ducts) from 13 human subjects. This atlas was developed using spatially registered and integrated technologies consisting of imaging mass spectrometry, multiplexed immunofluorescence, stained microscopy, and autofluorescence microscopy, to comprehensively probe large (i.e., centimeter-sized) areas of tissue. The cellular organization and lipid profiles of glomeruli, proximal tubules, distal tubules, and collecting ducts were discovered through these multimodal imaging data as well as their intra- and inter-subject variance. Relating the lipid profiles obtained from imaging mass spectrometry to distinct cell types obtained from immunofluorescence allowed us to hypothesize the functional role of specific phospholipids that have not previously been described. These hypotheses include subject characteristics, such as BMI and sex. The integrated data from the aforementioned datasets provide a valuable reference for kidney researchers, are publicly available through the NIH Human Biomolecular Atlas Program (https://portal.hubmapconsortium.org/), and discussed below. Single cell profiling of functionally cured Chronic Hepatitis B patients reveals the emergence of activated innate and an altered adaptive immune response in the intra-hepatic environment Hepatitis B surface antigen (HBsAg) loss or functional cure (FC), is considered the desirable therapeutic outcome for chronic hepatitis B (CHB) patients. However, the immuno-pathological biomarkers and underlying mechanisms remain unclear. Here we present a comprehensive single cell-transcriptomic atlas together with immune-phenotyping of disease-associated cell states (DACS) isolated from intra-hepatic tissue and matched PBMCs of either CHB or FC patients. We find that the intra-hepatic environment displays specific cell identities and molecular signatures that are distinct from PBMCs. FC is associated with emergence of an altered adaptive immune response marked by CD4 cytotoxic T lymphocytes (CD4-CTLs), and an activated innate response represented by liver-resident natural killer (LR-NK) cells. Overall, these findings provide novel insights into immuno-pathological cell states associated with FC that could serve as prognostic biomarkers. Multiplex knockout of trichome-regulating MYB duplicates in hybrid poplar using a single gRNA As the focus for CRISPR edited plants moves from proof-of-concept to real world applications, precise gene manipulation will increasingly require concurrent multiplex editing for polygenic traits. A common approach for editing across multiple sites is to design one gRNA per target; however, this complicates construct assembly and increases the possibility of off-target mutations. In this study, we utilized one gRNA to target MYB186, a known positive trichome regulator, as well as its paralogs MYB138 and MYB38 at a consensus site for mutagenesis in Populus tremula x P. alba INRA 717-1B4. Unexpected duplications of MYB186 and MYB138 resulted in a total of eight alleles for the three targeted genes in the hybrid poplar. Deep sequencing and PCR analyses confirmed editing across all eight targets in nearly all of the resultant glabrous mutants, ranging from small indels to large genomic dropouts, with no off-target activity detected at four potential sites. This highlights the effectiveness of a single gRNA targeting conserved exonic regions for multiplex editing. Additionally, cuticular wax and whole leaf analyses showed a complete absence of triterpenes in the trichomeless mutants, hinting at a previously undescribed role for the non-glandular trichomes of poplar.

ONE SENTENCE SUMMARYTargeting conserved sequences with a single gRNA allowed efficient mutagenesis of a multigene family and the recovery of trichomeless and triterpene-free poplar mutants. Orientation dependent proton transverse relaxation in the human brain white matter: The magic angle effect on a cylindrical helix PurposeTo overcome some limitations of prior orientation-dependent proton transverse relaxation formalisms in white matter (WM) with a novel framework based on the generalized magic angle effect function.

MethodsA cylindrical helix model was developed embracing anisotropic rotational and translational diffusion of restricted molecules in human brain WM, with the former characterized by an axially symmetric system. Transverse relaxation rates R2 and [Formula] were divided into isotropic [Formula] and anisotropic parts, [Formula], with  denoting an open angle and{varepsilon} 0 an orientation ({Phi}) offset from DTI-derived primary diffusivity direction. The proposed framework (Fit A) was compared with prior models without{varepsilon} 0 on previously published water and methylene proton transverse relaxation rates from developing, healthy, and pathological WM at 3T. Goodness of fit was represented by root-mean-square error (RMSE). F-test and linear correlation were used with statistical significance set to P [&le;] 0.05.

ResultsFit A significantly (P<0.01) outperformed prior models as demonstrated by reduced RMSEs, e.g., 0.349 vs. 0.724 in myelin water. Fitted{varepsilon} 0 was in good agreement with calculated{varepsilon} 0 from directional diffusivities. Compared with those from healthy adult, the fitted [Formula], and  from neonates were substantially reduced but{varepsilon} 0 increased, consistent with incomplete myelination. Significant positive [Formula] and negative ( and [Formula]) correlations were found with aging (demyelination) in elderly.

ConclusionThe developed framework can better characterize orientation dependences from a wide range of proton transverse relaxation measurements in human brain WM, shedding new light on myelin microstructural alterations at the molecular level. Flexible control of Pavlovian-instrumental transfer based on expected reward value The Pavlovian-instrumental transfer (PIT) paradigm is widely used to assay the motivational influence of reward-predictive cues, reflected by their ability to invigorate instrumental behavior. Leading theories of incentive learning assume that cues are assigned motivational properties based on the value of the rewards they predict. We outline an alternative account of PIT which recognizes that reward-predictive cues may suppress rather than motivate instrumental behavior under certain conditions. We posit that cues capable of triggering a strong reward expectancy will tend to inhibit instrumental behavior, which is exploratory by nature, in order to facilitate retrieval of the expected reward before it is lost or stolen. According to this view, the motivation to engage in instrumental behavior during a cue should be inversely related to the value of the predicted reward, since there is more to lose by failing to secure a high-value reward than a low-value reward. We tested this hypothesis in rats using a high-conflict PIT protocol which elicits competing instrumental and food-port entry responses. In Experiment 1, cues signaling different reward magnitudes (1, 3, or 9 pellets) differentially influenced these behaviors. Whereas the 1-pellet cue increased instrumental behavior, cues signaling 3 or 9 pellets suppressed instrumental behavior and elicited high levels of food-port activity. Experiment 2 found that reward-predictive cues suppressed instrumental behavior and increased food-port activity in a flexible manner that was disrupted by post-training reward devaluation. We discuss how the PIT task provides a useful tool for studying cognitive control over cue-motivated behavior in rodents. The obstacles and potential clues of prime editing applications in tomato, a dicot plant Precision genome editing is highly desired for crop improvement. The recently emerged CRISPR/Cas technology offers great potential applications in precision plant genome engineering. A prime editing (PE) approach combining a reverse transcriptase (RT) with a Cas9 nickase and a "priming" extended guide RNA has shown a high frequency for precise genome modification in mammalian cells and several plant species. Nevertheless, the applications of the PE approach in dicot plants are still limited and inefficient. We designed and tested prime editors for precision editing of a synthetic sequence in a transient assay and for desirable alleles of 10 loci in tomato by stable transformation. Our data obtained by targeted deep sequencing also revealed only low PE efficiencies in both the tobacco and tomato systems. Further assessment of the activities of the PE components uncovered potential reasons for the inefficiency of the PE complexes. Modifying the pegRNA sequences by shortening or introducing mismatches to the primer binding sequences (PBS) in order to reduce their melting temperatures (Tm) did not enhance the PE efficiency at the SlBMP21, SlALC and SlALS1 loci. Our data show challenges of PE approach in tomato, indicating a further improvement of the PE system for the successful applications such as use of improved expression systems. Our work provides an important clue for the successful application of the PE approach in crop improvement. Can double PPO mutations exist in the same allele and are such mutants functional? BackgroundResistance to PPO-inhibiting herbicides is primarily endowed by target site mutations at the PPO2 gene that compromise binding of the herbicide to the catalytic domain. In Amaranthus ssp. PPO2, the most prevalent target mutations are deletion of the G210 codon and the R128G and G339A substitutions. These mutations strongly affect the dynamic of the PPO2 binding pocket resulting in reduced affinity with the ligand. Here we investigated the likelihood of co-occurrence of the most widespread target site mutations in the same ppo2 allele.

ResultsPlants carrying R128G+/+ {Delta}G210+/-, where + indicates presence of the mutation, were crossed with each other. The ppo2 of the offspring was subjected to pyrosequencing and E. coli- based Sanger sequencing to determine mutation frequencies and allele co-occurrence. The data show that R128G {Delta}G210 can occur only in one allele; the second allele carries only one mutation. Double mutation in both alleles is less likely because of significant loss of enzyme activity. The segregation of offspring populations derived from a cross between heterozygous plants carrying {Delta}G210 G399A also showed no co-occurrence in the same allele. The offspring exhibited the expected mutation distribution patterns with few exceptions.

ConclusionsHomozygous double-mutants are not physiologically viable. Double-mutant plants can only exist in a heterozygous state. Alternatively, if two mutations are detected in one plant, each mutation would occur in a separate allele.

NomenclaturePalmer amaranth, Amaranthus palmeri S. Wats.; protoporphyrinogen oxidase, PPO; tall waterhemp, Amaranthus tuberculatus (Moq.) J.D.Sauer