Adversarial domain translation networks for fast and accurate integration of large-scale atlas-level single-cell datasets The rapid emergence of large-scale atlas-level single-cell RNA-seq datasets presents remarkable opportunities for broad and deep biological investigations through integrative analyses. However, harmonizing such datasets requires integration approaches to be not only computationally scalable, but also capable of preserving a wide range of fine-grained cell populations. We created Portal, a unified framework of adversarial domain translation to learn harmonized representations of datasets. With innovation in model and algorithm designs, Portal achieves superior performance in preserving biological variation during integration, while achieving integration of millions of cells in minutes with low memory consumption. We show that Portal is widely applicable to integrating datasets across samples, platforms and data types (including scRNA-seq, snRNA-seq and scATAC-seq). Finally, we demonstrate the power of Portal by applying it to the integration of cross-species datasets with limited shared information among them, elucidating biological insights into the similarities and divergences in the spermatogenesis process among mouse, macaque and human.
Drug-Target Binding Affinity Prediction Using Transformers Drug discovery is generally difficult, expensive, and low success rate. One of the essential steps in the early stages of drug discovery and drug repurposing is identifying drug-target interactions. Binding affinity indicates the strength of drug-target pair interactions. In this regard, several computational methods have been developed to predict the drug-target binding affinity, and the input representation of these models has been shown to be very effective in improving accuracy. Although the recent models predict binding affinity more accurate than the first ones, they need the structure of target proteins. Despite the strong interest in protein structure, there is a massive gap between known sequences and experimentally determined structures. Therefore, finding an appropriate presentation for drug and protein sequences is vital for drug-target binding affinity prediction. In this paper, our primary goal is to assess the drug and protein sequence representation for improving drug-target binding affinity prediction.
Lymph node swelling combined with temporary effector T cell retention aids T cell response in a model of adaptive immunity Swelling of lymph nodes is commonly observed during the adaptive immune response, yet the impact on T cell trafficking and subsequent immune response is not well known. To better understand the effect of macro-scale alterations, we developed an agent-based model of the lymph node para-cortex, describing T cell trafficking and response to antigen-presenting dendritic cells alongside swelling-induced changes in T cell recruitment and egress, and regulation of expression of egress-modulating T cell receptor Sphingosine-1-phosphate receptor-1. Analysis of effector T cell response under varying swelling conditions showed that swelling consistently aided T cell activation. However, subsequent effector CD8+ T cell production could be reduced if swelling occurred too early in the T cell proliferative phase or if T cell cognate frequency was low due to increased opportunity for T cell exit. Temporarily extending retention of newly differentiated effector T cells, mediated by Sphingosine-1-phosphate receptor-1 expression, mitigated any negative effects of swelling by allowing facilitation of activation to outweigh increased access to exit areas. These results suggest targeting temporary effector T cell retention and egress associated with swelling may offer new ways to modulate effector TC responses in, for example, immuno-suppressed patients and optimisation of vaccine design. Common Dynamic Determinants Govern Quorum Quenching Activity in N-terminal Serine Hydrolases Growing concerns about microbial antibiotic resistance have motivated extensive research into ways of overcoming antibiotic resistance. Quorum quenching (QQ) processes disrupt bacterial communication via quorum sensing, which enables bacteria to sense the surrounding bacterial cell density and markedly affects their virulence. Due to its indirect mode of action, QQ is believed to exert limited pressure on essential bacterial functions and may thus avoid inducing resistance. Although many enzymes display QQ activity against various bacterial signaling molecules, their mechanisms of action are poorly understood, limiting their potential optimization as QQ agents. Here we evaluate the capacity of three N-terminal serine hydrolases to degrade N-acyl homoserine lactones that serve as signaling compounds for Gram-negative bacteria. Using molecular dynamics simulations of the free enzymes and their complexes with two signaling molecules of different lengths, followed by quantum mechanics/molecular mechanics molecular dynamics simulations of their initial catalytic steps, we clarify the molecular processes underpinning their QQ activity. We conclude that all three enzymes degrade bacterial signaling molecules via similar reaction mechanisms. Moreover, we experimentally confirmed the activity of two penicillin G acylases from Escherichia coli (ecPGA) and Achromobacter spp. (aPGA), adding these biotechnologically well-optimized enzymes to the QQ toolbox. We also observed enzyme- and substrate-dependent differences in the catalytic actions of these enzymes, arising primarily from the distinct structures of their acyl-binding cavities and the dynamics of their molecular gates. As a consequence, the first reaction step catalyzed by ecPGA with a longer substrate had an elevated energy barrier because its shallow acyl binding site could not accommodate a productive substrate-binding configuration. Conversely, aPGA in complex with both substrates exhibited unfavorable energetics in both reaction steps due to the dynamics of the residues gating the acyl binding cavity entrance. Finally, the energy barriers of the second reaction step catalyzed by Pseudomonas aeruginosa acyl-homoserine lactone acylase with both substrates were higher than in the other two enzymes due to the unique positioning of Arg297{beta} in this enzyme. The discovery of these dynamic determinants will guide future efforts to design robust QQ agents capable of selectively controlling virulence in resistant bacterial species. Protein cost minimization promotes the emergence of coenzyme redundancy Coenzymes distribute a variety of chemical moieties throughout cellular metabolism, participating in group (e.g., phosphate, acyl) and electron transfer. For a variety of reactions requiring acceptors or donors of specific resources, there often exist degenerate sets of molecules (e.g., NAD(H) and NADP(H)) that carry out similar functions. Although the physiological roles of various coenzyme systems are well established, it is unclear what selective pressures may have driven the emergence of coenzyme redundancy. Here we use genome-wide metabolic modeling approaches to decompose the selective pressures driving enzymatic specificity for either NAD(H) or NADP(H) in the metabolic network of Escherichia coli. We found that few enzymes are thermodynamically constrained to using a single coenzyme, and in principle, a metabolic network relying on only NAD(H) is feasible. However, structural and sequence analyses revealed widespread conservation of residues that retain selectivity for either NAD(H) or NADP(H), suggesting that additional forces may shape specificity. Using a model accounting for the cost of oxidoreductase enzyme expression, we found that coenzyme redundancy universally reduces the minimal amount of protein required to catalyze coenzyme-coupled reactions, inducing individual reactions to strongly prefer one coenzyme over another when reactions are near thermodynamic equilibrium. We propose that protein minimization generically promotes coenzyme redundancy, and that coenzymes typically thought to exist in a single pool (e.g., CoA) may exist in more than one form (e.g., dephospho-CoA).

Significance statementMetabolism relies on a small class of molecules (coenzymes) that serve as universal donors and acceptors of key chemical groups and electrons. Although metabolic networks crucially depend on structurally redundant coenzymes (e.g., NAD(H) and NADP(H)) associated with different enzymes, the criteria that led to the emergence of this redundancy remain poorly understood. Our combination of modeling, and structural and sequence analysis indicates that coenzyme redundancy is not essential for metabolism, but rather an evolved strategy promoting efficient usage of enzymes when biochemical reactions are near equilibrium. Our work suggests that early metabolism may have operated with fewer coenzymes, and that adaptation for metabolic efficiency may have driven the rise of coenzyme diversity in living systems. Embracing imperfection: machine-assisted invertebrate classification in difficult datasets O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.
C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.
C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.
C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the  long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
C_LI MTG16 (CBFA2T3) regulates colonic epithelial differentiation, colitis, and tumorigenesis by repressing E protein transcription factors Aberrant epithelial differentiation and regeneration contribute to colon pathologies including inflammatory bowel disease (IBD) and colitis-associated cancer (CAC). MTG16 (CBFA2T3) is a transcriptional corepressor expressed in the colonic epithelium. MTG16 deficiency in mice exacerbates colitis and increases tumor burden in CAC, though the underlying mechanisms remain unclear. Here, we identified MTG16 as a central mediator of epithelial differentiation, promoting goblet and restraining enteroendocrine cell development in homeostasis and enabling regeneration following dextran sulfate sodium (DSS)-induced colitis. Transcriptomic analyses implicated increased E box-binding transcription factor (E protein) activity in MTG16-deficient colon crypts. Using a novel mouse model with a point mutation that disrupts MTG16:E protein complex formation (Mtg16P209T), we established that MTG16 exerts control over colonic epithelial differentiation and regeneration by repressing E protein-mediated transcription. Mimicking murine colitis, MTG16 expression was increased in biopsies from patients with active IBD compared to unaffected controls. Finally, uncoupling MTG16:E protein interactions only partially phenocopied the enhanced tumorigenicity of Mtg16-/- colon in the azoxymethane(AOM)/DSS-induced model of CAC, indicating that MTG16 protects from tumorigenesis through additional mechanisms. Collectively, our results demonstrate that MTG16, via its repression of E protein targets, is a key regulator of cell fate decisions during colon homeostasis, colitis, and cancer.

Graphical Abstract

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org.highwire.dtl.DTLVardef@21948borg.highwire.dtl.DTLVardef@9f60eeorg.highwire.dtl.DTLVardef@194b9fdorg.highwire.dtl.DTLVardef@13eb1a7_HPS_FORMAT_FIGEXP  M_FIG C_FIG Creatine transporter deficient rat model show motor dysfunction, cerebellar alterations and muscle creatine deficiency without muscle atrophy Creatine (Cr) is a nitrogenous organic acid and plays roles as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy and motor dysfunction. Among CCDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8Y389C knock-in (KI) rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunction, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain. 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. The perceptual relevance of the speech envelope-following response in normal hearing and age-related hearing impaired listeners The aim of this work was to investigate the perceptual relevance of the frequency following response to the syllable /da/ for speech intelligibility in noise based on age and hearing deficits. Recordings of the auditory evoked potential from young normal hearing (NH) and older individuals with both normal hearing and high-frequency (HF) hearing loss were analyzed. EFR metrics obtained in quiet and noise condition were calculated and correlated with speech reception. The envelope following responses were analyzed in terms of amplitude, latency and noise robustness. The response was first simulated to form predictions on the effect of cochlear synaptopathy and outer hair cell loss on the EFR. The experimental findings were in line with the computational predictions in the found observation that the EFR was reduced as a consequence of ageing and HF hearing loss. Both the audiogram and the speech EFR magnitude fell short in the individual prediction of SRT in stationary noise, but they accounted well for group performance. We also obtained within-group EFR latency with a cross covariance matrix. Validation of the method confirmed that speech EFR latency was predictive of click ABR Wave V peak latency. Moreover, statistical analysis not only showed that the robustness of the EFR obtained in the noise condition was dependent on the degree of high-frequency hearing loss in the older NH adults, but also dependent on the EFR magnitude in the NH younger adults. These findings provide evidence towards the important role of the EFR in speech-in-noise perception. Natural selection promotes the evolution of recombination 1: between the products of natural selection Shuffling ones genetic material with another individual seems a risky endeavor more likely to decrease than to increase offspring fitness. This intuitive argument is commonly employed to explain why the ubiquity of sex and recombination in nature is enigmatic. It is predicated on the notion that natural selection assembles selectively well-matched combinations of genes that recombination would break up resulting in low-fitness offspring - a notion often stated in the literature as a self-evident premise. We show however that, upon closer examination, this premise is flawed: we find to the contrary that natural selection in fact has an encompassing tendency to assemble selectively mismatched gene combinations; recombination breaks up these selectively mismatched combinations (on average), assembles selectively matched combinations, and should thus be favored. The new perspective our findings offer suggests that sex and recombination are not so enigmatic but are instead unavoidable byproducts of natural selection. In vitro maturation of Toxoplasma gondii bradyzoites in human myotubes and their metabolomic characterization The apicomplexan parasite Toxoplasma gondii forms bradyzoite-containing tissue cysts that cause chronic and drug-tolerant infections. However, current in vitro models do not allow long-term culture of these cysts to maturity. Here, we developed a human myotube-based in vitro culture model of functionally mature tissue cysts that are orally infectious to mice and tolerate exposure to a range of antibiotics and temperature stresses. Metabolomic characterization of purified cysts reveals global changes that comprise increased levels of amino acids and decreased abundance of nucleobase- and tricarboxylic acid cycle-associated metabolites. In contrast to fast replicating tachyzoite forms of T. gondii these tissue cysts tolerate exposure to the aconitase inhibitor sodium fluoroacetate. Direct access to persistent stages of T. gondii under defined cell culture conditions will be essential for the dissection of functionally important host-parasite interactions and drug evasion mechanisms. It will also facilitate the identification of new strategies for therapeutic intervention. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

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

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Genetic basis of a spontaneous mutation's expressivity Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutations expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutations expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation. 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. Engineered bacteria detect tumor DNA Advances in bacterial engineering have catalysed the development of living cell diagnostics and therapeutics1-3, including microbes that respond to diseases such as gut inflammation4, intestinal bleeding5, pathogens6 and hypoxic tumors7. Bacteria can easily access the entire gastrointestinal tract via oral administration8, and they can produce outputs that can be noninvasively measured in stool4 or urine7. Cellular memory, such as bistable switches4,9,10 or genomic rearrangement11, has been used to allow bacteria to store information over time. However, living biosensors have not yet been engineered to detect specific DNA sequences or mutations from outside the cell. Here, we engineer naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells and organoids. We characterize the functionality of the biosensors in vitro with co-culture assays and then validate in vivo with sensor bacteria delivered orally or rectally into mice injected with orthotopic donor CRC organoids. We observe horizontal gene transfer from the tumor to the sensor bacteria in vivo, allowing their detection in stool. The sensor bacteria achieved 100% discrimination between mice with and without CRC using both delivery methods. Our findings establish a framework for biosensing applications that require the detection of mutations or organisms within environments that are difficult to sample. In addition, the platform can be readily expanded to include in situ production and delivery of therapeutic payloads at the detection site. Host cell membrane capture by the SARS CoV-2 spike protein fusion intermediate Cell entry by SARS-CoV-2 is accomplished by the S2 subunit of the spike S protein on the virion surface by capture of the host cell membrane and fusion with the viral envelope. Capture and fusion require the prefusion S2 to transit to its potent, fusogenic form, the fusion intermediate (FI). However, the FI structure is unknown, detailed computational models of the FI are unavailable, and the mechanisms and timing of membrane capture and fusion are not established. Here, we constructed a full-length model of the CoV-2 FI by extrapolating from known CoV-2 pre- and postfusion structures. In atomistic and coarse-grained molecular dynamics simulations the FI was remarkably flexible and executed large bending and extensional fluctuations due to three hinges in the C-terminal base. Simulations suggested a host cell membrane capture time of [~] 2 ms. Isolated fusion peptide simulations identified an N-terminal helix that directed and maintained binding to the membrane but grossly underestimated the binding time, showing that the fusion peptide environment is radically altered when attached to its host fusion protein. The large configurational fluctuations of the FI generated a substantial exploration volume that aided capture of the target membrane, and may set the waiting time for fluctuation-triggered refolding of the FI that draws the viral envelope and host cell membrane together for fusion. These results describe the FI as a machinery designed for efficient membrane capture and suggest novel potential drug targets.



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org.highwire.dtl.DTLVardef@1374b59org.highwire.dtl.DTLVardef@133d21forg.highwire.dtl.DTLVardef@127f2ddorg.highwire.dtl.DTLVardef@1b9ab8f_HPS_FORMAT_FIGEXP  M_FIG C_FIG A platform of patient-derived microtumors identifies individual treatment responses and therapeutic vulnerabilities in ovarian cancer. BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses.

MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format.

ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.

Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment. The Alzheimer susceptibility gene BIN1 induces isoform-dependent neurotoxicity through early endosome defects The Bridging Integrator 1 (BIN1) gene is a major susceptibility gene for Alzheimers disease (AD). Deciphering its pathophysiological role is challenging due to its numerous isoforms. Here we observed in Drosophila that human BIN1 isoform1 (BIN1iso1) overexpression, contrary to BIN1iso8 and BIN1iso9, induced an accumulation of endosomal vesicles and neurodegeneration. Systematic search for endosome regulators able to prevent BIN1iso1-induced neurodegeneration indicated that a defect at the early endosome level is responsible for the neurodegeneration. In human induced neurons (hiNs) and cerebral organoids, BIN1 knock-out resulted in the narrowing of early endosomes. This phenotype was rescued by BIN1iso1 but not BIN1iso9 expression. Finally, BIN1iso1 overexpression also led to an increase in the size of early endosomes and neurodegeneration in hiNs. Altogether, our data demonstrate that the AD susceptibility gene BIN1, and especially BIN1iso1, contributes to early-endosome size deregulation, which is an early pathophysiological hallmark of AD pathology. Migrators Within Migrators: Exploring Transposable Element Dynamics in the Monarch Butterfly, Danaus plexippus BackgroundLepidoptera (butterflies and moths) are an important model system in ecology and evolution. A high-quality chromosomal genome assembly is available for the monarch butterfly (Danaus plexippus), but it lacks an in-depth transposable element (TE) annotation, presenting an opportunity to explore monarch TE dynamics and the impact of TEs on shaping the monarch genome.

ResultsWe find 6.21% of the monarch genome is comprised of TEs, a reduction of 6.85% compared to the original TE annotation performed on the draft genome assembly. Monarch TE content is low compared to two closely related species with available genomes, Danaus chrysippus (33.97% TE) and Danaus melanippus (11.87% TE). The biggest TE contributions to genome size in the monarch are LINEs and Penelope-like elements, and three newly identified families, r2-hero_dPle (LINE), penelope-1_dPle (Penelope-like), and hase2-1_dPle (SINE), collectively contribute 34.92% of total TE content. We find evidence of recent TE activity, with two novel Tc1 families rapidly expanding over recent timescales (tc1-1_dPle, tc1- 2_dPle). LINE fragments show signatures of genomic deletions indicating a high rate of TE turnover. We investigate associations between TEs and wing colouration and immune genes and identify a three-fold increase in TE content around immune genes compared to other host genes.

ConclusionsWe provide a detailed TE annotation and analysis for the monarch genome, revealing a considerably smaller TE contribution to genome content compared to two closely related Danaus species with available genome assemblies. We identify highly successful novel DNA TE families rapidly expanding over recent timescales, and ongoing signatures of both TE expansion and removal highlight the dynamic nature of repeat content in the monarch genome. Our findings also suggest that insect immune genes are promising candidates for future interrogation of TE-mediated host adaptation. A cell type-specific multiomics uncovers a guard cell-specific RAF15-SnRK2.6/OST1 kinase cascade Multicellular organisms such as plants contain different cell types with specialized functions. Analyzing the characteristics of each cell type reveals specific cell functions and enhances understanding of organization and function at the organismal level. Here we report a highly-sensitive and efficient cell type-specific multiomics pipeline, combining simplified flow cytometry-based cell sorting for fluorescent protoplasts and optimized nanoscale proteomics and metabolomics methods, which allow in-depth analysis of the proteomes and metabolomes of a particular cell type. Using this method, we quantitatively compared the proteomes and metabolomes of guard cells and mesophyll cells and revealed that the enrichment of signal transduction-related proteins enables guard cells to respond rapidly to various environmental stimuli. We uncovered a guard cell-specific kinase cascade whereby RAF15 and OST1 mediate ABA-induced stomatal closure. This pipeline can be applied to various cell types in plant or non-plant systems to learn how cells function in highly organized multicellular organisms. 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. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. 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. TRIM28-dependent SUMOylation protects the adult ovary from the testicular pathway Gonadal sexual fate in mammals is determined during embryonic development and must be actively maintained in adulthood. In the mouse ovary, oestrogen receptors and FOXL2 protect ovarian granulosa cells from transdifferentiation into Sertoli cells, their testicular counterpart. However, the mechanism underlying their protective effect is unknown. Here, we show that TRIM28 is required to prevent female-to-male sex reversal of the mouse ovary after birth. We found that upon loss of Trim28, ovarian granulosa cells transdifferentiate to Sertoli cells through an intermediate cell type, different from gonadal embryonic progenitors. TRIM28 is recruited on chromatin in the proximity of FOXL2 to maintain the ovarian pathway and to repress testicular-specific genes. The role of TRIM28 in ovarian maintenance depends on its E3-SUMO ligase activity that regulates the sex-specific SUMOylation profile of ovarian-specific genes. Our study identifies TRIM28 as a key factor in protecting the adult ovary from the testicular pathway. Agrobacterium mediated transformation and deciphering SNPs in TaLr67 gene homeologs for gene editing in wheat. Diseases adversely affect grain yield of crop plants. Leaf rust is a major disease of wheat. As race-specific resistance breaks down, introduction of newer sources of resistance often from older accessions is necessary. Linkage drag from the donor accessions adversely impacts grain yield. As a result, CIMMYT breeding effort has shifted to using durable resistance, also referred to as race non-specific host resistance, which allows slow rusting but maintains grain yield. One of the key genes for durable resistance is Lr67 and the resistant form of this gene is absent in CIMMYT elite lines. Hence, we have initiated efforts to convert the susceptible copy of Lr67 into its resistant form directly in these elite lines using gene editing. This would eliminate backcrossing and thus save time as well as eliminate linkage drag that would accompany the resistant copy of the gene if it were to be introgressed from an older accession. As first steps, we have isolated and sequenced the genomic copies from each of the A, B, and D genome of the Lr67 gene from three elite lines and an experimental line. Identification of more than 50 single nucleotide polymorphisms (SNPs) in the open reading frames (ORF) among these lines would be useful in designing the guide RNA molecules with precision. Further, we have streamlined genetic transformation of these elite lines, a prerequisite step for gene editing.