CIITA induces expression of MHC-I and MHC-II in transmissible cancers MHC-I and MHC-II molecules are critical components of antigen presentation and T cell immunity to pathogens and cancer. The two monoclonal transmissible devil facial tumours (DFT1, DFT2) exploit MHC-I pathways to overcome immunological anti-tumour and allogeneic barriers. This exploitation underpins the ongoing transmission of DFT cells across the wild Tasmanian devil population. We have previously shown that constitutive expression of NLRC5 can induce stable upregulation of MHC-I on DFT1 and DFT2 cells, but unlike IFNG-treated cells, NLRC5 does not upregulate PDL1. MHC-II expression is crucial for CD4+ T cell activation and is primarily confined to haematopoietic antigen presenting cells. Transcriptomic analysis of DFT1 and DFT2 cell lines showed that several genes of the MHC-I and MHC-II pathways were upregulated in response to constitutive overexpression of the class II transactivator (CIITA) gene. This was further supported by upregulation of MHC-I protein on DFT1 and DFT2 cells, but interestingly MHC-II protein was upregulated only on DFT1 cells. The functional significance of the MHC upregulation on DFT cells was shown using serum from devils with natural or immunotherapy-induced DFT1 regressions; binding of serum IgG was stronger in CIITA-transfected cells than wild type cells, but was less than binding to NLRC5 transfected cells. This new insight into regulation of MHC-I and MHC-II in cells that naturally overcome allogeneic barriers can inform vaccine, immunotherapy, and tissue transplant strategies for human and veterinary medicine.
Circulating multimeric immune complexes drive immunopathology in COVID-19 A dysregulated immune response with high levels of SARS-CoV-2 specific IgG antibodies characterizes patients with severe or critical COVID-19. Although a robust IgG response is traditionally considered to be protective, excessive triggering of activating Fc-gamma-receptors (Fc{gamma}Rs) could be detrimental and cause immunopathology. Here, we document that patients who develop soluble circulating IgG immune complexes (sICs) during infection are subject to enhanced immunopathology driven by Fc{gamma}R activation. Utilizing cell-based reporter systems we provide evidence that sICs are predominantly formed prior to a specific humoral response against SARS-CoV-2. sIC formation, together with increased afucosylation of SARS-CoV-2 specific IgG eventually leads to an enhanced CD16 (Fc{gamma}RIII) activation of immune cells reaching activation levels comparable active systemic lupus erythematosus (SLE) disease. Our data suggest a vicious cycle of escalating immunopathology driven by an early formation of sICs in predisposed patients. These findings reconcile the seemingly paradoxical findings of high antiviral IgG responses and systemic immune dysregulation in severe COVID-19.

Clinical implicationsThe identification of sICs as drivers of an escalating immunopathology in predisposed patients opens new avenues regarding intervention strategies to alleviate critical COVID-19 progression.

Graphical abstract

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org.highwire.dtl.DTLVardef@b4616corg.highwire.dtl.DTLVardef@682d1aorg.highwire.dtl.DTLVardef@16946cborg.highwire.dtl.DTLVardef@a6ef7d_HPS_FORMAT_FIGEXP  M_FIG C_FIG A vicious cycle of immunopathology in COVID-19 patients is driven by soluble multimeric immune complexes (sICs). SARS-CoV-2 infection triggers sIC formation in prone individuals. Activation of Fc{gamma}RIII/CD16 expressing immune cells by sICs precedes a humoral response to SARS-CoV2 infection. sICs and infection add to IgG afucosylation, further enhancing Fc{gamma}RIII/CD16 activation by opsonized targets. High inflammation induces further sIC mediated immune cell activation ultimately leading to an escalating immunopathology.
Principles of mRNA targeting via the Arabidopsism6A-binding protein ECT2 Specific recognition of N6-methyladenosine (m6A) in mRNA by RNA-binding proteins containing a YT521-B homology (YTH) domain is important in eukaryotic gene regulation. The Arabidopsis YTH-domain protein ECT2 is thought to bind to mRNA at URU(m6A)Y sites, yet RR(m6A)CH is the canonical m6A consensus site in all eukaryotes and ECT2 functions require m6A binding activity. Here, we apply iCLIP (individual-nucleotide resolution cross-linking and immunoprecipitation) and HyperTRIBE (targets of RNA-binding proteins identified by editing) to define high-quality target sets of ECT2, and analyze the patterns of enriched sequence motifs around ECT2 crosslink sites. Our analyses show that ECT2 does in fact bind to RR(m6A)CH. Pyrimidine-rich motifs are enriched around, but not at m6A-sites, reflecting a preference for N6-adenosine methylation of RRACH/GGAU islands in pyrimidine-rich regions. Such motifs, particularly oligo-U and UNUNU upstream of m6A sites, are also implicated in ECT2 binding via its intrinsically disordered region (IDR). Finally, URUAY-type motifs are enriched at ECT2 crosslink sites, but their distinct properties suggest function as sites of competition between binding of ECT2 and as yet unidentified RNA-binding proteins. Our study provides coherence between genetic and molecular studies of m6A-YTH function in plants, and reveals new insight into the mode of RNA recognition by YTH-domain-containing proteins. Oct1 recruits the histone lysine demethylase Utx to promote lineage specification The pathways used by cells to transition between undifferentiated, pluripotent state and tissue-specific states are incompletely understood. Here we show that the widely-expressed transcription factor Oct1/Pou2f1 activates silent, developmental lineage-appropriate genes to "canalize" developmental progression. Using Oct1 inducible knockout embryonic stem cells, we show that that Oct1 deficiency impairs mesodermal and terminal muscle differentiation in a manner that can be rescued by Oct1 retroviral expression. Using bulk RNA-seq, we show that mesoderm-specific genes are not correctly induced early in the differentiation timecourse. Single-cell gene expression profiling reveals that Oct1-deficient cells lose coherence in temporal induction of lineage programs, and show inappropriate developmental lineage branching resulting in poorly differentiated cells state with epithelial characteristics and hallmarks of oxidative stress. In embryonic stem cells, Oct1 co-binds with Oct4 to genes critical for mesoderm induction. The Utx/Kdm6a histone lysine demethylase also binds to many of these genes, and using a prototypic Pax3 gene we show that Oct1 recruits Utx to remove inhibitory H3K27me3 marks and activate expression. The specificity of the ubiquitous Oct1 protein for mesodermal genes can be explained by cooperative interactions with lineage-driving Smad transcription factors, as we show that Smad and Oct binding sites frequently coexist mesoderm-specific genes, that Oct1 and Smad3 interact, and that the sites and factors act cooperatively at the Myog enhancer. Overall, these results identify Oct1 as a key mediator of the induction of mesoderm lineage-specific genes. Multiparametric profiling of cellular lipid metabolism in hypercholesterolemia Systematic insight into cellular dysfunctions can improve understanding of disease etiology, risk assessment and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validated this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrated lipid storage data into a novel readout, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlated positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explained hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking from a few mls of blood and is applicable to dissect metabolic disorders, such as hypercholesterolemia.

MotivationWe have limited information on how cellular lipid uptake and processing differ between individuals and influence the development of metabolic diseases, such as hypercholesterolemia. Available assays are labor intensive, require skilled personnel and are difficult to scale to higher throughput, making it challenging to obtain systematic functional cell-based data from individuals. To overcome this problem, we established a scalable automated analysis pipeline enabling reliable quantification of multiple cellular readouts, including lipid uptake, storage and mobilization, from different white blood cell populations. This approach provides new personalized insights into the cellular basis of hypercholesterolemia and obesity.

Graphical Abstract

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org.highwire.dtl.DTLVardef@9222c1org.highwire.dtl.DTLVardef@27e289org.highwire.dtl.DTLVardef@89ba82org.highwire.dtl.DTLVardef@33c9cd_HPS_FORMAT_FIGEXP  M_FIG C_FIG Greater spear nosed bats in Panama do not use social proximity to improve foraging efficiency Group foraging animals may change their spatial relationships in response to the resource landscape. The strength of social network ties across foraging groups could then reflect the energy balance of individual group members through their effect on foraging efficiency. Greater spear-nosed bats (Phyllostomus hastatus) live in social groups where unrelated females develop group-specific social calls, defend each others offspring, and are hypothesized to coordinate social foraging to feed on balsa flowers. To test if social groups forage together, and if this increases foraging efficiency, we tracked 18 individuals from three social groups of P. hastatus on Isla Colon, Panama using high frequency GPS for 1 - 3 days each. We found that individuals commuted alone but then joined group members in small foraging patches with high densities of flowering balsas, 25 km from their roost on the mainland. Proximity-based social network measures did not predict foraging efficiency or energy expenditure, but individuals with higher social associations spent more time outside of the cave. Individuals did not coordinate movement, but close proximity among individuals increased resting bout duration and synchrony, particularly when in the same patch. These results show that stronger social proximity associations were more closely tied to resting behavior, and indicate that factors other than increased feeding efficiency may structure network relationships of group members while foraging.

Lay SummarySocial foraging can increase foraging efficiency on hard-to-find food sources. Miniaturized high-frequency GPS allowed us to test this on groups of greater spear-nosed bats. We estimated food intake rates, energy expenditure, and the strength of bat social relationships. In contrast to our expectations, we did not find a relationship between bat social relationships and energy expenditure or foraging efficiency. However, bats took longer resting breaks when group members were close. Why these bats commute 25 km individually across the ocean to then forage near each other thus requires further investigation. 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. Changes to the mtDNA copy number during yeast culture growth We show that the mtDNA copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest ([~]10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains, but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype. Estimating the fundamental niche: accounting for the uneven availability of existing climates Studies that question important conceptual and methodological aspects of the field of ecological niche modeling (and species distribution modeling) have cast doubts on whether it is possible to estimate the fundamental niche of a species using presence-only data. The main limitation in niche estimation is that presence data come from the realized niche, which is only a subset of the fundamental niche. Most of the existing methods lack the ability to overcome this limitation and therefore fit niches that resemble the realized niche. To obtain a more accurate estimate of the fundamental niche, we propose using the geographic region that is accessible to a species (based on its dispersal ability) to determine a sampling distribution, in environmental space, from which we can quantify the likelihood of observing a particular environmental combination in a sample of presence points. We incorporate this sampling distribution into a multivariate normal model (i.e., a Mahalanobis distance model) by creating a weight function that modifies the probabilities of observing different environmental combinations in a sample of presences. This modification accounts for the uneven availability of environmental conditions. We show that the parameters of this weighted-normal model can be approximated with a maximum likelihood estimation approach; and then used to draw ellipsoids (confidence regions) that represent the fundamental niche of the species. We illustrate the application of our model with two worked examples. First, we use presence data for an invasive species and an accessible area that includes only its native range to evaluate whether the fitted model predicts confirmed establishments of the species outside its native range. Second, we use presence data for closely related species with known accessible areas to demonstrate how the different dispersal abilities of the species constrain a classic Mahalanobis distance model. Overall, we show that accounting for the distribution of environmental conditions that are accessible to a species indeed affects the estimation of the ellipsoids used to model its fundamental niche. Onlinemeta: A Web Server For Meta-Analysis Based On R-shiny Meta-analysis is a common statistical method used to summarize multiple studies that cover the same topic. It can provide less biased results and explain heterogeneity between studies. Although there exists a variety of meta-analysis software, they are rarely both convenient to use and capable of comprehensive analytical functions. As a result, we established a meta-analysis web tool called Meta-Analysis Online (Onlinemeta). Onlinemeta includes both risk bias analysis and meta-analysis. The risk bias analysis tool can produce heatmaps and histograms, whereas the meta-analysis tool can be used to analyze dichotomous variables, single-armed dichotomous variables, continuous variables, single-armed continuous variables, survival data, and diagnostic experiments. In addition, it can be used to generate forest plots, funnel plots, SROC curve, and crosshair plots. Onlinemeta can be found at the following address: https://smuonco.Shinyapps.io/Onlinemeta/. Preprints in motion: tracking changes between preprint posting and journal publication during a pandemic Amidst the COVID-19 pandemic, preprints in the biomedical sciences are being posted and accessed at unprecedented rates, drawing widespread attention from the general public, press and policymakers for the first time. This phenomenon has sharpened longstanding questions about the reliability of information shared prior to journal peer review. Does the information shared in preprints typically withstand the scrutiny of peer review, or are conclusions likely to change in the version of record? We assessed preprints from bioRxiv and medRxiv that had been posted and subsequently published in a journal through 30th April 2020, representing the initial phase of the pandemic response. We utilised a combination of automatic and manual annotations to quantify how an article changed between the preprinted and published version. We found that the total number of figure panels and tables changed little between preprint and published articles. Moreover, the conclusions of 7.2% of non-COVID-19-related and 17.2% of COVID-19-related abstracts undergo a discrete change by the time of publication, but the majority of these changes do not qualitatively change the conclusions of the paper. Hidden dynamics of human proteasome autoregulation during protein degradation The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation. Short-term instantaneous prophylaxis and efficient treatment against SARS-CoV-2 in hACE2 mice conferred by an intranasal nanobody (Nb22) Current COVID-19 vaccines need to take at least one month to complete inoculation and then become effective. Around 51% global population are still not fully vaccinated. Instantaneous protection is an unmet need among those who are not fully vaccinated. In addition, breakthrough infections caused by SARS-CoV-2 are widely reported. All these highlight the unmet needing for short-term instantaneous prophylaxis (STIP) in the communities where SARS-CoV-2 is circulating. Previously, we reported nanobodies isolated from an alpaca immunized with the spike protein, exhibiting ultrahigh potency against SARS-CoV-2 and its variants. Herein, we found that Nb22, among our previously reported nanobodies, exhibited ultrapotent neutralization against Delta variant with an IC50 value of 0.41 ng/ml (5.13 pM). Furthermore, the crystal structural analysis revealed that the binding of Nb22 to WH01 and Delta RBDs both effectively blocked the binding of RBD to hACE2. Additionally, intranasal Nb22 exhibited protection against SARS-CoV-2 Delta variant in the post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP). Of note, intranasal Nb22 also demonstrated high efficacy against SARS-CoV-2 Delta variant in STIP for seven days administered by single dose and exhibited long-lasting retention in the respiratory system for at least one month administered by four doses, providing a means of instantaneous short-term prophylaxis against SARS-CoV-2. Thus, ultrahigh potency, long-lasting retention in the respiratory system as well as stability at room-temperature make the intranasal or inhaled Nb22 to be a potential therapeutic or STIP agent against SARS-CoV-2.

Brief summaryNb22 exhibits ultrahigh potency against Delta variant in vitro and is exploited by crystal structural analysis; furthermore, animal study demonstrates high effectiveness in the treatment and short-term instantaneous prophylaxis in hACE2 mice via intranasal administration.

HighlightsO_LINb22 exhibits ultrapotent neutralization against Delta variant with an IC50 value of 0.41 ng/ml (5.13 pM).
C_LIO_LIStructural analysis elucidates the ultrapotent neutralization of Nb22 against Delta variant.
C_LIO_LINb22 demonstrates complete protection in the treatment of Delta variant infection in hACE2 transgenic mice.
C_LIO_LIWe complete the proof of concept of STIP against SARS-CoV-2 using intranasal Nb22 with ultrahigh potency and long-lasting retention in respiratory system.
C_LI

Graphic Abstract

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org.highwire.dtl.DTLVardef@144516corg.highwire.dtl.DTLVardef@3dc17forg.highwire.dtl.DTLVardef@6a8962org.highwire.dtl.DTLVardef@619cd7_HPS_FORMAT_FIGEXP  M_FIG C_FIG Embryonic exposure to cannabidiol disrupts active neural circuits, an effect increased by Δ9-tetrahydrocannabinol and involving CB1R and CB2R in zebrafish In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. A class of identifiable phylogenetic birth-death models In a striking result, Louca and Pennell (2020) recently proved that a large class of phylogenetic birth-death models are statistically unidentifiable from lineage-through-time (LTT) data: any pair of sufficiently smooth birth and death rate functions is "congruent" to an infinite collection of other rate functions, all of which have the same likelihood for any LTT vector of any dimension. As Louca and Pennell argue, this fact has distressing implications for the thousands of studies that have utilized birth-death models to study evolution.

In this paper, we qualify their finding by proving that an alternative and widely used class of birth-death models is indeed identifiable. Specifically, we show that piecewise constant birth-death models can, in principle, be consistently estimated and distinguished from one another, given a sufficiently large extant time tree and some knowledge of the present-day population. Subject to mild regularity conditions, we further show that any unidentifiable birth-death model class can be arbitrarily closely approximated by a class of identifiable models. The sampling requirements needed for our results to hold are explicit, and are expected to be satisfied in many contexts such as the phylodynamic analysis of a global pandemic. From fitting the average to fitting the individual: A cautionary tale for mathematicalmodelers An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying the individualized best-fit parameters, and extrapolating from there to make personalized treatment recommendations. Our analyses show the potentially problematic nature of this approach, as predicted personalized treatment response proved to be sensitive to the fitting methodology utilized. We also demonstrate how a small amount of the right additional experimental measurements could go a long way to improve consistency in personalized fits. Finally, we show how quantifying the robustness of the average response could also help improve confidence in personalized treatment recommendations.

Author summaryAs we enter the era of healthcare where personalized medicine becomes a more common approach to treating cancer patients, harnessing the power of mathematical models will only become more essential. Using a preclinical dataset on cancer immunotherapy, we explore the challenges and limitations that arise when trying to move from fitting and making predictions for the population-level average, to fitting and making predictions for an individual. We find that the standard of approach of picking a single fitting methodology and a single cost function may end up having limited predictive value when applied to individual data. We also show how having a small amount of the right additional experimental data, and establishing the robustness of average treatment response, can help improve confidence in personalized model predictions. SERCA function is impaired in skeletal and cardiac muscles from young DBA/2J mdx mice The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. An alignment free approach confirms semantic properties of species proteomes Alignment-based methods dominate molecular biology. However, by primarily allowing one-to-one comparisons, these methods are focused on a gene-centered viewpoint and lack the broad context essential to analyze how complex biological systems function and evolve. In actuality, a gene is part of genome where more than one sequence contributes to the functional network and evolutionary trajectory of the cell. The need for conservation of established interactions, is arguably more important to the evolutionary success of species than conservation of individual function. To test whether such contextual information exists, a distributional semantics method - Latent Semantic Analysis (LSA), was applied to thousands of species proteomes. Using natural language processing, Latent Taxonomic Signatures (LTSs) were identified that outperformed existing alignment-based BLAST methods when random protein sequences were being mapped to annotated taxonomy according to GenBank. LTSs are a novel proteome distributed feature, suggesting the existence of evolutionary constraints imposed on individual proteins by their proteome context. Even orphan proteins are exhibiting LTSs, which makes their uniqueness linked to a specific taxonomic level questionable. Unlike more simple bias, LTSs represent a self-similarity pattern, where random sets of species proteins show the same statistical properties of a complete proteome at many scales. Natural language processing and machine learning provide insights not easily discernable using alignment based methods suggestive there is more to species related differences than just translational optimization. Macroscopic control of synchronous electrical signaling with chemically-excited gene expression Excitable cells can convert electrical signals into chemical outputs to facilitate the active transport of information across larger distances. This electrical-to-chemical conversion requires a tightly regulated expression of ion channels. Alterations of ion channel expression provide landmarks of numerous pathological diseases, such as cardiac arrhythmia, epilepsy, or cancer. Although the activity of ion channels can be locally regulated by external light or chemical stimulus, it remains challenging to coordinate the expression of ion channels on extended spatial-temporal scales in a non-invasive manner. Here, we have engineered yeast S. cerevisiae to read and convert local chemical concentrations into a dynamic electrical field distributed across cell populations. The core mechanism encodes a chemically-excitable dual-feedback gene circuit that precisely tunes the expression domain of potassium channels, globally coordinating cyclic firing of the plasma membrane potential (PMP). We demonstrate that this mechanism leverages an engineered constitutively open bacterial potassium channel KcsA to directly couple chemical stimuli with ion flux through gene expression and it can interface with the host ion channels through the pulsatile production of toxins. Our study provides a robust synthetic transcriptional toolbox underlying the conversion of local chemical environments into spatiotemporally organized electrical impulses for various cellular engineering, synthetic biology, and potential therapeutic applications. Prostaglandin EP3 Receptor signaling is required to prevent insulin hypersecretion and metabolic dysfunction in a non-obese mouse model of insulin resistance When homozygous for the LeptinOb mutation (Ob), Black-and-Tan Brachyury (BTBR) mice become morbidly obese and severely insulin resistant, and by 10 weeks of age, frankly diabetic. Previous work has shown Prostaglandin EP3 Receptor (EP3) expression and activity is up-regulated in islets from BTBR-Ob mice as compared to lean controls, actively contributing to their beta-cell dysfunction. In this work, we aimed to test the impact of beta-cell-specific EP3 loss on the BTBR-Ob phenotype by crossing Ptger3 floxed mice with the Rat insulin promoter (RIP)-CreHerr driver strain. Instead, germline recombination of the floxed allele in the founder mouse - an event whose prevalence we identified as directly associated with underlying insulin resistance of the background strain - generated a full-body knockout. Full-body EP3 loss provided no diabetes protection to BTBR-Ob mice, but, unexpectedly, significantly worsened BTBR-lean insulin resistance and glucose tolerance. This in vivo phenotype was not associated with changes in beta-cell fractional area or markers of beta-cell replication ex vivo. Instead, EP3-null BTBR-lean islets had essentially uncontrolled insulin hypersecretion. The selective up-regulation of constitutively-active EP3 splice variants in islets from young, lean BTBR mice as compared to C57BL/6J, where no phenotype of EP3 loss has been observed, provides a potential explanation for the hypersecretion phenotype. In support of this, high islet EP3 expression in Balb/c females vs. Balb/c males was fully consistent with their sexually-dimorphic metabolic phenotype after loss of EP3-coupled Gz protein. Taken together, our findings provide a new dimension to the understanding of EP3 as a critical brake on insulin secretion.

New and NoteworthyIslet Prostaglandin EP3 receptor (EP3) signaling is well-known as up-regulated in the pathophysiological conditions of type 2 diabetes, contributing to beta-cell dysfunction. Unexpected findings in mouse models of non-obese insulin sensitivity and resistance provide a new dimension to our understanding of EP3 as a key modulator of insulin secretion. A previously-unknown relationship between mouse insulin resistance and the penetrance of Rat insulin promoter-driven germline floxed allele recombination is critical to consider when creating beta-cell-specific knockouts.

For Table of Contents Use Only

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org.highwire.dtl.DTLVardef@15cf1d5org.highwire.dtl.DTLVardef@108f565org.highwire.dtl.DTLVardef@126e479org.highwire.dtl.DTLVardef@61fdf8_HPS_FORMAT_FIGEXP  M_FIG C_FIG Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Water levels primarily drive variation in photosynthesis and nutrient use of scrub Red Mangroves in the southeastern Florida Everglades We investigated how mangrove-island micro-elevation (i.e., habitat: center vs. edge) affects tree physiology in a scrub mangrove forest of the southeastern Everglades. We measured leaf gas exchange rates of scrub Rhizophora mangle L. trees monthly during 2019, hypothesizing that CO2 assimilation (Anet) and stomatal conductance (gsw) would decline with increasing water levels and salinity, expecting more-considerable differences at mangrove-island edges than centers, where physiological stress is greatest. Water levels varied between 0 and 60 cm from the soil surface, rising during the wet season (May-October) relative to the dry season (November-April). Porewater salinity ranged from 15 to 30 ppt, being higher at mangrove-island edges than centers. Anet maximized at 15.1 {micro}mol m-2 s-1, and gsw was typically <0.2 mol m-2 s-1, both of which were greater in the dry than the wet season and greater at island centers than edges, with seasonal variability being roughly equal to variation between habitats. After accounting for season and habitat, water level positively affected Anet in both seasons but did not affect gsw. Our findings suggest that inundation stress (i.e., water level) is the primary driver of variation in leaf gas exchange rates of scrub mangroves in the Florida Everglades, while also constraining Anet more than gsw. The interaction between inundation stress due to permanent flooding and habitat varies with season as physiological stress is alleviated at higher-elevation mangrove-island center habitats during the dry season. Freshwater inflows during the wet season, increase water levels and inundation stress at higher-elevation mangrove-island centers, but also potentially alleviate salt and sulfide stress in soils. Thus, habitat heterogeneity leads to differences in nutrient and water acquisition and use between trees growing in island centers versus edges, creating distinct physiological controls on photosynthesis, which likely affect carbon flux dynamics of scrub mangroves in the Everglades. 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. Theory and Simulations of condensin mediated loop extrusion in DNA Condensation of hundreds of mega-base-pair-long human chromosomes in a small nuclear volume is a spectacular biological phenomenon. This process is driven by the formation of chromosome loops. The ATP consuming motor, condensin, interacts with chromatin segments to actively extrude loops. Motivated by real-time imaging of loop extrusion (LE), we created an analytically solvable model, predicting the LE velocity and step size distribution as a function of external load. The theory fits the available experimental data quantitatively, and suggests that condensin must undergo a large conformational change, induced by ATP binding, bringing distant parts of the motor to proximity. Simulations using a simple model confirm that the motor transitions between an open and a closed state in order to extrude loops by a scrunching mechanism, similar to that proposed in DNA bubble formation during bacterial transcription. Changes in the orientation of the motor domains are transmitted over ~ 50 nm, connecting the motor head and the hinge, thus providing an allosteric basis for LE. In vitro culture of freshly isolated Trypanosoma brucei brucei bloodstream forms results in gene copy-number changes. Most researchers who study unicellular eukaryotes work with an extremely limited number of laboratory-adapted isolates that were obtained from the field decades ago, but the effects of passage in laboratory rodents, and adaptation to in vitro culture, have been little studied. For example, the vast majority of studies of Trypanosoma brucei biology have concentrated on just two strains, Lister 427 and EATRO1125, which were taken from the field over half a century ago and have since have undergone innumerable passages in rodents and culture. We here describe two new Trypanosoma brucei brucei strains. MAK65 and MAK98, which have undergone only 3 rodent passages since isolation from Ugandan cattle. High-coverage sequencing revealed that adaptation of the parasites to culture was accompanied by changes in gene copy numbers. T. brucei has so far been considered to be uniformly diploid, but we also found trisomy of chromosome 5 not only in one Lister 427 culture, but also in the MAK98 field isolate. Trisomy of chromosome 6, and increased copies of other chromosome segments, were also seen in established cultured lines. The two new T. brucei strains should be useful to researchers interested in trypanosome differentiation and pathogenicity. Initial results suggested that the two strains have differing infection patterns in rodents. MAK65 is uniformly diploid and grew more reproducibly in bloodstream-form culture than MAK98. Dimerization of kringle 1 domain from hepatocyte growth factor/scatter factor provides a potent minimal MET receptor agonist. Hepatocyte Growth Factor/Scatter Factor (HGF/SF) and its cognate receptor MET play several essential roles in embryogenesis and regeneration in post-natal life of epithelial organs such as liver, kidney, lung, and pancreas, prompting a strong interest in harnessing HGF/SF-MET signalling for regeneration of epithelial organs after acute or chronic damage. The limited stability and tissue diffusion of native HGF/SF, however, which reflect the tightly controlled, local mechanism of action of the morphogen, have led to a major search for HGF/SF mimics for therapy. In this work, we describe the rational design, production and characterisation of K1K1, a novel minimal MET agonist consisting of two copies of the kringle 1 domain of HGF/SF placed in tandem. K1K1 is highly stable and displays biological activities equivalent or superior to native HGF/SF in a variety of in vitro assay systems and in a mouse model of liver disease. These data suggest that this engineered ligand may find wide applications in acute and chronic diseases of the liver and other epithelial organs dependent on MET activation.