RapidoPGS: A rapid polygenic score calculator for summary GWAS data without a test dataset MotivationPolygenic scores (PGS) aim to genetically predict complex traits at an individual level. PGS are typically trained on genome-wide association summary statistics and require an independent test dataset to tune parameters. More recent methods allow parameters to be tuned on the training data, removing the need for independent test data, but approaches are computationally intensive. Based on fine-mapping principles, we present RapidoPGS, a flexible and fast method to compute PGS requiring summary-level GWAS datasets only, with little computational requirements and no test data required for parameter tuning.

ResultsWe show that RapidoPGS performs slightly less well than two out of three other widely-used PGS methods (LDpred2, PRScs, and SBayesR) for case-control datasets, with median r2 difference: -0.0092, -0.0042, and 0.0064, respectively, but up to 17,000-fold faster with reduced computational requirements. RapidoPGS is implemented in R and can work with user-supplied summary statistics or download them from the GWAS catalog.

Availability and implementationOur method is available with a GPL license as an R package from GitHub.
The quantitative genetics of the prevalence of infectious diseases: hidden genetic variation due to Indirect Genetic Effects dominates heritable variation and response to selection Infectious diseases have profound effects on life, both in nature and agriculture. Despite the availability of well-established epidemiological theory, however, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of the transmission dynamics of infectious diseases for heritable variation and response to selection of the host population, our current theoretical framework of quantitative genetics excludes these dynamics. As a consequence, we do not know which genetic effects of the host population determine the prevalence of an infection, and have no concepts of breeding value and heritable variation for endemic prevalence.

Here we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for R0 and for the endemic prevalence of an infectious disease. We first identify the genetic factors that determine the prevalence of an infection, using an approach founded in epidemiological theory. Subsequently we investigate the population level consequences of individual genetic variation, both for R0 and for the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for both prevalence and individual binary disease status, and show that these parameters depend strongly on the level of the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases when prevalence approaches zero, while heritability of individual disease status goes to zero. As a consequence, response of prevalence to selection accelerates considerably when prevalence goes down, in contrast to predictions from classical theory. Finally, we show that most of the heritable variation for the endemic prevalence of an infection is hidden due to indirect genetic effects, suggesting a key role for kin-group selection both in the evolutionary history of current populations and for genetic improvement strategies in animals and plants.
Destructive fishing - A ubiquitously used but vague term? Usage and impacts across academic research, media and policy The term "destructive fishing" appears in multiple international policy instruments intended to improve outcomes for marine biodiversity, coastal communities and sustainable fisheries. However, the meaning of "destructive fishing" is often vague, limiting effectiveness in policy. Therefore, in this study we systematically reviewed the use of "destructive fishing" in three record types: academic literature, media articles, and policy documents between 1976-2020. A more detailed analysis was performed on sub-sets of these records, considering the extent to which the term is characterised, geographic distribution of use, and specific impacts and practices associated with the term. We found that use of "destructive fishing" relative to the generic term  fisheries has increased since the 1990s. Records focused predominantly on fishing practices in South-eastern Asia, followed by Southern Asia and Europe. The term was characterised in detail in only 15% of records. Habitat damage and blast/poison fishing were the most associated ecological impacts and gear/practices, respectively. Bottom trawling and unspecified net fishing were regularly linked to destructive fishing. Importantly, the three record types use the term differently. Academic literature tends to specifically articulate the negative impacts, while media articles focus generally on associated gears/practices. Significant regional variation also exists in how the term is used and what phenomena it is applied to. This study provides evidence and recommendations to inform stakeholders in any future pursuit of a unified definition of "destructive fishing" to support more meaningful implementation of global sustainability goals. Decoding regulatory specificity of human ribosomal proteins Human ribosomes, made of around 80 ribosomal proteins (RPs) and four ribosomal RNAs, have long been thought as uniform passive protein-making factories with little regulatory function. Recently, accumulating evidence showed heterogeneity of RP composition in ribosomes responsible for regulating gene expression in development and tumorigenesis. However, a comprehensive understanding of regulatory spectrum of RPs is still lacking. In this study, we conducted a systematic survey of regulatory specificity of human RPs on global gene expression. We quantified translational and transcriptional changes of gene expression upon deficiency of 75 RPs, including 44 from the large subunit (60S) and 31 from the small subunit (40S), by ribosomal profiling and RNA sequencing analysis. We showed that RP deficiency induced diverse expression changes, particularly at the translational level. RPs were subjected to co-translational regulation under ribosomal stress where deficiency of the 60S and the 40S RPs had opposite effects on the two subunits. RP deficiency perturbed expression of genes related to cell cycle, cellular metabolism, signal transduction and development. Deficiency of RPs from the 60S led to a greater repression effect on cell growth than that from the 40S by perturbing P53 signaling and cell cycle pathways. To demonstrate functional specificity of RPs, we showed that RPS8 deficiency stimulated cellular apoptosis and RPL13 or RPL18 deficiency promoted cellular senescence. We also showed that RPL11 and RPL15 played important roles in retina development and angiogenesis, respectively. Overall, our study demonstrated a widespread regulatory role of RPs in controlling cellular activity, providing an important resource which can offer novel insights into ribosome regulation in human diseases and cancer. Serological fingerprints link antiviral activity of therapeutic antibodies to affinity and concentration We assessed the affinities of the therapeutic monoclonal antibodies (mAbs) cilgavimab, tixagevimab, sotrovimab, casirivimab, and imdevimab to the receptor binding domain (RBD) of wild type, Delta, and Omicron spike. The Omicron RBD affinities of cilgavimab, tixagevimab, casirivimab, and imdevimab decreased by at least two orders of magnitude relative to their wild type equivalents, whereas sotrovimab binding was less severely impacted. These affinity reductions correlate with reduced antiviral activities of these antibodies, suggesting that simple affinity measurements can serve as an indicator for activity before challenging and time-consuming virus neutralization assays are performed. We also compared the properties of these antibodies to serological fingerprints (affinities and concentrations) of wild type RBD specific antibodies in 74 convalescent sera. The affinities of the therapeutic mAbs to wild type and Delta RBD were in the same range as the polyclonal response in the convalescent sera indicative of their high antiviral activities against these variants. However, for Omicron RBD, only sotrovimab retained affinities that were within the range of the polyclonal response, in agreement with its high activity against Omicron. Serological fingerprints thus provide important context to affinities and antiviral activity of mAb drugs and could guide the development of new therapeutics. Nuclear Progestin Receptor Mediated Linkage of Blood Coagulation and Ovulation Ovulation is a dramatic remodeling process that includes rupture of blood capillaries and clotting, but coagulation is not thought to directly regulate this process. Herein, we report remarkable increases of coagulation factors V (f5, [~]3145-fold) and tissue factor (f3a, [~]120-fold) in zebrafish ovarian follicle cells during ovulation. This increase was mediated through the nuclear progestin receptor (Pgr), which is essential for ovulation in zebrafish, and was totally abolished in ovarian follicular cells from pgr-/- mutants. In addition, promoter activities of f5 and f3a were significantly enhanced by progestin (DHP) via Pgr. Similar regulation of human F5 promoter activity was induced via human PGRB, suggesting a conserved mechanism. Site-directed mutagenesis of the zebrafish f5 promoter further demonstrated a direct regulation of coagulation factors via progestin response elements. Moreover, a stark increase of erythrocytes occurred in capillaries meshed in wildtype preovulatory follicles but was absent in pgr-/- mutants. Interestingly, anticoagulants significantly inhibited ovulation both in vitro and in vivo, respectively. Furthermore, reduced fecundity was observed in f5+/- female zebrafish. Taken together, our study provides plausible evidence for steroid regulation of coagulation factors, and a new hypothesis for blood clotting triggered ovulation in vertebrates. Coevolution of relative brain size and life expectancy in parrots Previous studies have demonstrated a correlation between longevity and brain size in a variety of taxa. Little research has been devoted to understanding this link in parrots; yet parrots are well-known for both their exceptionally long lives and cognitive complexity. We employed a large-scale comparative analysis that investigated the influence of brain size and life history variables on longevity in parrots. Specifically, we addressed two hypotheses for evolutionary drivers of longevity: the Cognitive Buffer Hypothesis, which proposes that increased cognitive abilities enable longer life spans, and the Expensive Brain Hypothesis, which holds that increases in life span are caused by prolonged developmental time of, and increased parental investment in, large brained offspring. We estimated life expectancy from detailed zoo records for 133,818 individuals across 244 parrot species. Using a principled Bayesian approach that addresses data uncertainty and imputation of missing values, we found a consistent correlation between relative brain size and life expectancy in parrots. This correlation was best explained by a direct effect of relative brain size. Notably, we found no effects of developmental time, clutch size, or age at first reproduction. Our results suggest that selection for enhanced cognitive abilities in parrots have in turn promoted longer lifespans. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. The Functional Nanopore Screen: A Versatile High-throughput Assay to Study and Engineer Protein Nanopores in Escherichia coli Nanopores comprise a versatile class of membrane proteins that carry out a range of key physiological functions and are increasingly developed for different biotechnological applications. Yet, a capacity to study and engineer protein nanopores by combinatorial means has so far been hampered by a lack of suitable assays that combine sufficient experimental resolution with throughput. Addressing this technological gap, the Functional Nanopore (FuN) screen now provides a quantitative and dynamic read-out of nanopore assembly and function in E. coli. The assay is based on genetically-encoded fluorescent protein sensors that resolve the nanopore-dependent influx of Ca2+ across the inner membrane of E. coli. Illustrating its versatile capacity, the FuN screen is first applied to dissect the molecular features that underlie the assembly and stability of nanopores formed by the S2168 holin. In a subsequent step, nanopores are engineered by recombining the transmembrane module of S2168 with different ring-shaped oligomeric protein structures that feature defined hexa-, hepta- and octameric geometries. Library screening highlights substantial plasticity in the ability of the S2168 transmembrane module to oligomerize in alternative geometries while the functional properties of the resultant nanopores can be fine-tuned through the identity of the connecting linkers. Overall, the FuN screen is anticipated to facilitate both fundamental studies and complex nanopore engineering endeavors with many potential applications in biomedicine, biotechnology and synthetic biology. Artificial seawater based long-term culture of colonial ascidians Tunicates are highly diverse marine invertebrate filter-feeders that are vertebrates closest relatives. These organisms, despite a drastically different body plan during their adulthood, have a tissue complexity related to that of vertebrates. Ascidians, which compose most of the Tunicata, are benthic sessile hermaphrodites that reproduce sexually through a motile tadpole larval stage. Over half of the known ascidians species are able to reproduce asexually by budding, typically leading to the formation of colonies where animals, called zooids, are interconnected through an external vascular system. In addition, colonial ascidians are established models for important biological processes including allorecognition, immunobiology, aging, angiogenesis and whole-body regeneration. However, the current paucity in breeding infrastructures limits the study of these animals to coastal regions.

To promote a wider scientific spreading and popularity of colonial ascidians, we have developed a flexible recirculating husbandry setup for their long-term in-lab culture. Our system is inspired both by the flow-through aquariums used by coastal ascidian labs, as well as by the recirculating in-lab systems used for zebrafish research. Our hybrid system thus combines colony breeding, water filtering and food culturing in a semi-automated system where specimens develop on hanging microscopy glass slides. Temperature, light/dark cycles, flow speed and feeding rates can be controlled independently in four different breeding environments to provide room for species-specific optimization as well as for running experiments. This setup is complemented with a quarantine for the acclimatization of wild isolates.

Herein we present our success in breeding Botrylloides diegensis, a species of colonial ascidians, for more than 3 years in recirculating artificial seawater over 600 km away from their natural habitat. We show that colonies adapt well to in-lab culturing provided that a suitable marine microbiome is present, and that a specific strain can be isolated, propagated and efficiently used for research over prolonged periods of time. The flexible and modular structure of our system can be scaled and adapted to the needs of specific species, such as Botryllus schlosseri, as well as of particular laboratory spaces. Overall, we show that Botrylloides diegensis can be proficiently bred in-land and suggest that our results can be extended to other species of colonial ascidians to promote research on these fascinating animals.

HighlightsO_LIFirst artificial seawater based recirculating aquaculture for colonial ascidians
C_LIO_LIOver 3 years of continuous breeding
C_LIO_LISemi-automated setup with minimized maintenance
C_LIO_LIGood biomass production for strain propagation
C_LIO_LI4 different culture conditions for optimized breeding for species of interest
C_LI Vocal markers of autism: assessing the generalizability of machine learning models Machine learning (ML) approaches show increasing promise in their ability to identify vocal markers of autism. Nonetheless, it is unclear to what extent such markers generalize to new speech samples collected e.g., using a different speech task or in a different language. In this paper, we systematically assess the generalizability of ML findings across a variety of contexts.

We train promising published ML models of vocal markers of autism on novel cross-linguistic datasets following a rigorous pipeline to minimize overfitting, including cross-validated training and ensemble models. We test the generalizability of the models by testing them on i) different participants from the same study, performing the same task; ii) the same participants, performing a different (but similar) task; iii) a different study with participants speaking a different language, performing the same type of task.

While model performance is similar to previously published findings when trained and tested on data from the same study (out-of-sample performance), there is considerable variance between studies. Crucially, the models do not generalize well to different, though similar, tasks and not at all to new languages. The ML pipeline is openly shared.

Generalizability of ML models of vocal markers of autism is an issue. We outline three recommendations for strategies researchers could take to be more explicit about generalizability and improve it in future studies.

LAY SUMMARYMachine learning approaches promise to be able to identify autism from voice only. These models underestimate how diverse the contexts in which we speak are, how diverse the languages used are and how diverse autistic voices are. Machine learning approaches need to be more careful in defining their limits and generalizability. A Physiometric Investigation of Inflammatory Composites: Comparison of A Priori Aggregates, Empirically-identified Factors, and Individual Proteins Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor- (TNF-), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an "a priori"/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the "a priori"/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory. CsrA-controlled proteins reveal new dimensions of Acinetobacter baumannii desiccation tolerance Hospital environments are excellent reservoirs for the opportunistic pathogen Acinetobacter baumannii in part because it is exceptionally tolerant to desiccation. We found that relative to other A. baumannii strains, the virulent strain AB5075 was strikingly desiccation resistant at 2% relative humidity (RH), suggesting that its a good model for studies of the functional basis of this trait. Consistent with results from other A. baumannii strains at 30% RH, we found the global post-transcriptional regulator CsrA to be critically important for desiccation tolerance of AB5075 at 2% RH. To identify CsrA-controlled proteins that may contribute to desiccation tolerance we used proteomics to identify proteins that were differentially present in wild type and csrA mutant cells. Subsequent mutant analysis revealed nine genes that were required for wild type levels of desiccation tolerance, five of which had modest phenotypes. Catalase and a universal stress protein gene were moderately important for desiccation tolerance and two genes of unknown function had very strong desiccation phenotypes. The predicted amino acid sequence of one of these genes predicts an intrinsically disordered protein. This category of proteins is widespread in eukaryotes but less so in prokaryotes. Our results suggest there may be mechanisms responsible for desiccation tolerance that have not previously been explored in bacteria.

IMPORTANCEAcinetobacter baumannii is commonly found in terrestrial environments but can cause nosocomial infections in very sick patients. A factor that contributes to the prevalence of A. baumannii in hospital settings is that it is intrinsically resistant to dry conditions. Here, we established the virulent strain A. baumannii AB5075 as a model for studies of desiccation tolerance at very low relative humidity. Our results show that this trait depends on two proteins of unknown function, one of which is predicted to be an intrinsically disordered protein. This category of protein is critical for the small animals named tardigrades to survive desiccation. Our results suggest that A. baumannii may have novel strategies to survive desiccation that have not previously been seen in bacteria. "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. The DC1 domain protein BINUCLEATE POLLEN is required for pollen development in Arabidopsis thaliana Development of the male gametophyte is a tightly regulated process that requires precise control of cell division and gene expression. A relevant aspect to understand the events underlying pollen development regulation constitutes the identification and characterization of the genes required for this process. In this work we showed that the DC1 domain protein BINUCLEATE POLLEN (BNP) is essential for pollen development and germination. Pollen grains carrying the defective BNP allele failed to complete mitosis II and are impaired in pollen germination. By yeast two hybrid screening and bimolecular fluorescence complementation assays, we identified a set of BNP-interacting proteins. Among confirmed interactors we found NAC family transcriptional regulators Vascular plant One-Zinc finger 1 (VOZ1) and VOZ2. VOZ1 localization changes during pollen development, moving to the vegetative nucleus at the tricellular stage. We observed that this relocalization requires BNP, as in their absence in pollen from bnp/BNP plants, VOZ1 nuclear localization resulted impaired. As voz1voz2 double mutants showed the same developmental defect observed in bnp pollen grains, we propose that BNP requirement to complete microgametogenesis could be linked to its interaction with VOZ1/2 proteins. BNP could have a role of scaffold protein, recruiting VOZ1/2 to the endosomal system into assemblies that are required for their further translocation to the nucleus, where they act as transcriptional regulators. Temporal Scaling of Human Scalp-Recorded Potentials Much of human behaviour is governed by common processes that unfold over varying timescales. Standard event-related potential analysis assumes fixed-latency responses relative to experimental events. However, recent single unit recordings in animals have revealed neural activity scales to span different durations during behaviours demanding flexible timing. Here, we employed a general linear modelling approach using a novel combination of fixed-duration and variable-duration regressors to unmix fixed-time and scaled-time components in human magneto/electroencephalography (M/EEG) data. We use this to reveal consistent temporal scaling of human scalp-recorded potentials across four independent EEG datasets, including interval perception, production, prediction and value-based decision making. Between-trial variation in the temporally scaled response predicts between-trial variation in subject reaction times, demonstrating the relevance of this temporally scaled signal for temporal variation in behaviour. Our results provide a general approach for studying flexibly timed behaviour in the human brain. 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. Mechanical bistability of the mesoderm epithelium facilitates mesoderm invagination during Drosophila gastrulation Apical constriction driven by non-muscle myosin II ("myosin") provides a well-conserved mechanism to mediate epithelial folding. It remains unclear how contractile forces near the apical surface of a cell sheet drive out-of-the-plane bending of the sheet and whether myosin contractility is required throughout folding. By optogenetic-mediated acute inhibition of myosin, we find that during Drosophila mesoderm invagination, myosin contractility is critical to prevent tissue relaxation during the early, "priming" stage of folding but is dispensable for the actual folding step after the tissue passes through a stereotyped transitional configuration. The binary response suggests that the mesoderm is mechanically bistable during gastrulation. Combined modeling analysis and experimental measurements suggest that the observed mechanical bistability may arise from apicobasal shrinkage of the surrounding ectoderm, which promotes mesoderm invagination by facilitating a buckling transition. Our results suggest that Drosophila mesoderm invagination requires a joint action of local myosin contractility and mechanical bistability of the epithelium to trigger epithelial buckling. Hepatic MIR20B promotes nonalcoholic fatty liver disease by suppressing PPARA BackgroundNon-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation and imbalances in lipid metabolism in the liver. Although nuclear receptors (NRs) play a crucial role in hepatic lipid metabolism, the underlying mechanisms of NR regulation in NAFLD remain largely unclear.

MethodsUsing network analysis and RNA-seq to determine the correlation between NRs and microRNA in human NAFLD patients, we revealed that MIR20B specifically targets PPARA. MIR20B mimic and anti-MIR20B were administered to human HepG2 and Huh-7 cells and mouse primary hepatocytes as well as high fat diet (HFD)- or methionine-deficient diet (MCD)-fed mice to verify the specific function of MIR20B in NAFLD. We tested the inhibition of the therapeutic effect of a PPAR agonist, fenofibrate, by MIR20B and the synergic effect of combination of fenofibrate with anti-MIR20B.

ResultsWe revealed that MIR20B specifically targets PPARA through miRNA regulatory network analysis of nuclear receptor genes in NAFLD. The expression of MIR20B was upregulated in free fatty acid (FA)- treated hepatocytes and the livers of both obesity-induced mice and NAFLD patients. Overexpression of MIR20B significantly increased hepatic lipid accumulation and triglyceride levels. Furthermore, MIR20B significantly reduced FA oxidation and mitochondrial biogenesis by targeting PPARA. In MIR20B-introduced mice, the effect of fenofibrate to ameliorate hepatic steatosis was significantly suppressed. Finally, inhibition of MIR20B significantly increased FA oxidation and uptake, resulting in improved insulin sensitivity and a decrease in NAFLD progression. Moreover, combination of fenofibrate and anti-MIR20B exhibited the synergic effect on improvement of NAFLD in MCD-fed mice.

ConclusionsTaken together, our results demonstrate that the novel MIR20B targets PPARA, plays a significant role in hepatic lipid metabolism, and present an opportunity for the development of novel therapeutics for NAFLD.

FundingThis research was funded by Korea Mouse Phenotyping Project (2016M3A9D5A01952411), the National Research Foundation of Korea (NRF) grant funded by the Korea government (2020R1F1A1061267, 2018R1A5A1024340, NRF-2021R1I1A2041463, 2020R1I1A1A01074940), and the Future-leading Project Research Fund (1.210034.01) of UNIST. Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for clinical sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNA) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell-type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy, especially real-time medical applications. Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring Indirect wildlife population surveying largely depends upon counts of artefacts of behavior (e.g., nests or dung). Likelihood to encounter these artefacts is derived from both artefact production and decay, and variability in artefact production behavior is considered to contribute minimally to inaccuracy in wildlife estimation. Here we demonstrate how ignoring behavioral variability contributes to significant population misestimation, using an example of an endangered ape, the bonobo (Pan paniscus). Until now, a single estimate of (i.e., nest construction) has been used to extrapolate bonobo densities, assumed to be broadly representative of bonobo sign production behavior. We estimated nest construction rate across seasons and social groups at the Kokolopori Bonobo Reserve, DRC and find that nest construction rates in bonobos to be highly variable across populations as well as seasonal. Failure to account for this variability led to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and at worst as high as 80%. With this example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises the ability to estimate both relative and absolute wildlife abundances. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability can play upon wildlife population estimation. Our results underline the importance of observational research to wildlife monitoring schemes as a critical but overlooked component of conservation management. We extensively discuss the various avenues through which behavioral variability is likely to impact wildlife monitoring accuracy and precision and propose potential avenues for accounting for behavioral variability in wildlife monitoring. Embedded 3D printing in self-healing annealable composites for precise patterning of functionally mature human neural constructs Human in vitro models of neural tissue with controllable cellular identity, tunable microenvironment, and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing in jammed microgel supports (i.e., granular gels) holds great promise as it allows precise and programmable patterning of extremely soft and compliant tissue constructs. However, in contrast to the vast material landscape available for bulk hydrogels, granular printing support formulations are restricted to a handful of materials without the ability for facile adjustment of biofunctional properties of the cellular microenvironment. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, we present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise freeform patterning of human stem cells and consequent generation and long-term maintenance of mature subtype-specific neurons that extend projections within the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular channels. Due to its modularity, SHAPE biomanufacturing toolbox not only offers a solution for functional modeling of mechanically sensitive neural constructs, but also has potential to be applied to a wide range of biomaterials with different crosslinking mechanisms to model tissues and diseases where recapitulation of complex architectural features and topological cues is essential. Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harbouring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define three compositional  tissue-states rooted in cohabitation of cell-types and transcriptional states. These comprise a state featuring A) abundant normal brain microenvironment cells, B) reactive/inflamed brain microenvironment, and C) cellular/proliferative tumor. All these states exhibited variable degrees of infiltration by glioma cells. Spatial transcriptomics confirmed that the cell-types and transcriptomics states which compositionally cohabitate tissue states also colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. We found that enrichment of tissue state B signature correlated with shorter survival. Importantly, we found that our compositionally defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes resembling those seen in neurodegeneration, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to the glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries. Can single-component protein condensates form multiphase architectures? Phase-separated biomolecular condensates that contain multiple coexisting phases are widespread in vitro and in cells. Multiphase condensates emerge readily within multi-component mixtures of biomolecules (e.g. proteins and nucleic acids) when the different components present sufficient physicochemical diversity (e.g. in inter-molecular forces, structure, and chemical composition) to sustain separate coexisting phases. Because such diversity is highly coupled to the solution conditions (e.g. temperature, pH, salt, composition), it can manifest itself immediately from the nucleation and growth stages of condensate formation, develop spontaneously due to external stimuli, or progressively as the condensates age. Here, we investigate thermodynamic factors that can explain the intrinsic transformation of single-component condensates into multiphase architectures during the nonequilibrium process of ageing. We develop a multiscale model that integrates atomistic simulations of proteins, sequence-dependent coarse-grained simulations of condensates, and a minimal model of dynamically ageing condensates with non-conservative inter-molecular forces. Our nonequilibrium simulations of condensate ageing predict that single-component condensates that are initially homogeneous and liquid-like can transform into gel-core/liquid-shell or liquid-core/gel-shell multiphase condensates as they age, due to gradual and irreversible enhancement of inter-protein interactions. The type of multiphase architecture is determined by the ageing mechanism, the molecular organization of the gel and liquid phases, and the chemical make up of the protein. Notably, we predict that inter-protein disorder-to-order transitions within the prion-like domains of intracellular proteins could lead to the required non-conservative enhancement of inter-molecular interactions. Our study, therefore, predicts a potential mechanism

Significance StatementBiomolecular condensates are highly diverse systems spanning not only homogeneous liquid droplets, but also gels, glasses, and even multiphase architectures that contain various coexisting liquid-like and/or gel-like inner phases. Multiphase architectures form when the different biomolecular components in a multi-component condensate establish sufficiently imbalanced inter-molecular forces to sustain different coexisting phases. While such a requirement seems, at first glance, impossible to fulfil for a condensate formed exclusively of chemically-identical proteins (i.e., single-component), our simulations predict conditions under which this may be possible. During condensate ageing, a sufficiently large imbalance in inter-molecular interactions can emerge intrinsically from the accumulation of protein structural transitions--driving even single-component condensates into nonequilibrium liquid-core/gel-shell or gel-core/liquid-shell multiphase architectures. Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling framework, LK-DFBA, that addresses a key gap: capturing metabolite dynamics and regulation while retaining a potentially scalable linear programming structure. Key to this frameworks success are the linear kinetics and regulatory constraints imposed on the system. However, while the linearity of these constraints reduces computational complexity, it may not accurately capture the behavior of many biochemical systems. Here, we developed three new classes of LK-DFBA constraints to better model interactions between metabolites and the reactions they regulate. We tested these new approaches on several synthetic and biological systems, and also performed the first-ever comparison of LK-DFBA predictions to experimental data. We found that no single constraint approach was optimal across all systems examined, and systems with the same topological structure but different parameters were often best modeled by different types of constraints. However, we did find that the optimal constraint approach was generally robust to local perturbations of the system, indicating that just a single wild-type dataset could allow identification of the ideal constraint for a given system. These results suggest that the availability of multiple constraint approaches will allow LK-DFBA to model a wider range of metabolic systems. CRCM5484: A BET- BDII Selective Compound With Differential Anti-Leukemic Drug Modulation Differentially screening the Fr-PPIChem chemical library on the BET BRD4-BDII versus -BDI bromodomains led to the discovery of a BDII selective tetrahydropyridothienopyrimidinone (THPTP)-based compound. Structure-activity relationship (SAR) and hit-to-lead approaches allowed us to develop CRCM5484, a potent inhibitor of BET proteins with a preferential and 475-fold selectivity for the second bromodomain of the BRD3 protein (BRD3-BDII) over its first bromodomain (BRD3-BDI). Its very low activity was demonstrated in various cell-based assays, corresponding with recent data describing other selective BDII compounds. However, screening on a drug sensitivity and resistance-profiling platform revealed its ability to modulate the anti-leukemic activity in combination with various FDA-approved and/or in-development drugs in a cell- and context-dependent differential manner. Altogether, the results confirm the originality of the THPTP molecular mode of action in the BD cavity and its potential as starting scaffold for the development of potent and selective bromodomain inhibitors.