Plant host shift: The viability and persistence of a polyphagous, non-native insect Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.
Continuous land cover change detection in a critically endangered shrubland ecosystem using neural networks Existing efforts to continuously land cover change using satellite image time-series have mostly focused on forested ecosystems in the tropics and northern hemisphere. The notable difference in reflectance that occurs following deforestation allows land cover change to be detected with relative accuracy. Less progress has been made in detecting change in low productivity, disturbanceprone vegetation such as grasslands and shrublands, where natural dynamics can be difficult to distinguish from habitat loss. Renosterveld is a hyperdiverse, critically endangered shrubland ecosystem in South Africa with less than 5-10% of its original extent remaining in small, highly fragmented patches. I demonstrate that direct classification of satellite image time series using neural networks can accurately detect the transformation of Renosterveld within a few days of its occurrence, and that trained models are suitable for operational continuous monitoring. A dataset of precisely dated vegetation change events between 2016 and 2021 was obtained from daily, high resolution Planet labs satellite data. This dataset was then used to train and evaluate 1D convolutional neural networks and Transformers to continuously detect land cover change events in multivariate time-series of vegetation activity of Sentinel 2 satellite data as it becomes available. The best model correctly identified 89% of land cover change events at the pixel-level, achieving a f-score of 0.93, a 79% improvement over the f-score of 0.52 achieved using a method designed for forested ecosystems based on trend analysis. Models have been deployed to operational use and are producing updated detections of habitat loss every 10 days. There is great potential for supervised approaches to continuous monitoring of habitat loss in ecosystems with complex natural dynamics. A key limiting step is the development of accurately dated datasets of land cover change events with which to train machine learning classifiers.
Modeling miRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses. Estimating cell-type-specific gene co-expression networks from bulk gene expression data with an application to Alzheimer's disease Inferring and characterizing gene co-expression networks has led to important insights on the molecular mechanisms of complex diseases. Most co-expression analyses to date have been performed on gene expression data collected from bulk tissues with different cell type compositions across samples. As a result, the co-expression estimates only offer an aggregate view of the underlying gene regulations and can be confounded by heterogeneity in cell type compositions, failing to reveal gene coordination that may be distinct across different cell types. In this paper, we describe a flexible framework for estimating cell-type-specific gene co-expression networks from bulk sample data, without making specific assumptions on the distributions of gene expression profiles in different cell types. We develop a novel sparse least squares estimator, referred to as CSNet, that is efficient to implement and has good theoretical properties. Using CSNet, we analyzed the bulk gene expression data from a cohort study on Alzheimers disease and identified previously unknown cell-type-specific co-expressions among Alzheimers disease risk genes, suggesting cell-type-specific disease pathology for Alzheimers disease. Mitofusin 1 and 2 regulation of mitochondrial DNA content is a critical determinant of glucose homeostasis The dynamin-like GTPases Mitofusin 1 and 2 (Mfn1 and Mfn2) are essential for mitochondrial function, which has been principally attributed to their regulation of fission/fusion dynamics. Here, we report that Mfn1 and 2 are critical for glucose-stimulated insulin secretion (GSIS) primarily through control of mitochondrial DNA (mtDNA) content. Whereas Mfn1 and Mfn2 individually were dispensable for glucose homeostasis, combined Mfn1/2 deletion in {beta}-cells reduced mtDNA content, impaired mitochondrial morphology and networking, and decreased respiratory function, ultimately resulting in severe glucose intolerance. Importantly, gene dosage studies unexpectedly revealed that Mfn1/2 control of glucose homeostasis was dependent on maintenance of mtDNA content, rather than mitochondrial structure. Mfn1/2 maintain mtDNA content by regulating the expression of the crucial mitochondrial transcription factor Tfam, as Tfam overexpression ameliorated the reduction in mtDNA content and GSIS in Mfn1/2-deficient {beta}-cells. Thus, the primary physiologic role of Mfn1 and 2 in {beta}-cells is coupled to the preservation of mtDNA content rather than mitochondrial architecture, and Mfn1 and 2 may be promising targets to overcome mitochondrial dysfunction and restore glucose control in diabetes. Common variants in breast cancer risk loci predispose to distinct tumor subtypes BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction. Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC array A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enabling directional sensitivity and scalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting. Non-targeted multimodal metabolomics and lipidomics data from ovine rumen fluid fractions BackgroundMetabolomics is a powerful and sensitive approach for investigating low molecular weight metabolite profiles present in rumen biofluids to identify potential roles of metabolites in rumen microbiome and understanding host-level regulatory mechanisms associated with animal production.

FindingsRumen samples from sheep grazed on a mixed ryegrass and clover pasture diet, were fractionated based on molecular weight and analysed using metabolomics and lipidomics to detect the small molecules present in ovine rumen fluid fractions.

ConclusionsUntargeted metabolomics provides a detailed snapshot of the ovine ruminal fluid metabolome that can be used as reference for future studies on ovine rumen fluid or as a comparator for other ruminant species. All data and metadata are available for download in the MetaboLights database. Ribosome actuator via the SpoT/ppGpp pathway to mitigate gene overexpression burden Gene overexpression causes a burden on ribosomes, which decreases the expression of other genes and growth rate. Here, we engineer a genetic ribosome actuator that increases gene expression rate and growth rate by over 150% and 80%, respectively. The actuator expresses the hydrolysis domain of the SpoT enzyme (SpoTH) in a bacterial strain with high basal levels of ppGpp, thus increasing ribosome availability. We use this actuator in a feedforward control arrangement, wherein SpoTH is co-expressed with a gene of interest (GOI). Without SpoTH co-expression, activation of the GOI decreases the expression of a constitutive gene and growth rate by over 80% and 40%, respectively. By contrast, with SpoTH co-expression, the ribosome binding site (RBS) of SpoTH can be tuned to achieve inappreciable change of either the expression of the constitutive gene or growth rate when the GOI is activated to the same level. We finally employ the actuator to keep growth rate constant while expressing dCas9 to a level that would otherwise decrease growth rate by more than 40% due to toxicity. This actuator will be relevant in applications where high cellular protein concentrations are desired without growth defects or global reduction of gene expression. A novel nongenetic murine model of hyperglycemia and hyperlipidemia-associated aggravated atherosclerosis ObjectiveAtherosclerosis, the main pathology underlying cardiovascular diseases is accelerated in diabetic patients. Genetic mouse models require breeding efforts which are time-consuming and costly. Our aim was to establish a new nongenetic model of inducible metabolic risk factors that mimics hyperlipidemia, hyperglycemia, or both and allows the detection of phenotypic differences dependent on the metabolic stressor(s).

Methods and ResultsWild-type mice were injected with gain-of-function PCSK9D377Y (proprotein convertase subtilisin/kexin type 9) mutant adeno-associated viral particles (AAV) and streptozotocin and fed either a high-fat diet (HFD) for 12 or 20 weeks or a high-cholesterol/high-fat diet (Paigen diet, PD) for 8 weeks. To evaluate atherosclerosis, two different vascular sites (aortic sinus and the truncus of the brachiocephalic artery) were examined in the mice. Combined hyperlipidemic and hyperglycemic (HGHCi) mice fed a HFD or PD displayed characteristic features of aggravated atherosclerosis when compared to hyperlipidemia (HCi HFD or PD) mice alone. Atherosclerotic plaques of HGHCi HFD animals were larger, showed a less stable phenotype (measured by the increased necrotic core area, reduced fibrous cap thickness, and less -SMA-positive area) and had more inflammation (increased plasma IL-1{beta} level, aortic pro-inflammatory gene expression, and MOMA-2-positive cells in the BCA) after 20 weeks of HFD. Differences between the HGHCi and HCi HFD models were confirmed using RNA-seq analysis of aortic tissue, revealing that significantly more genes were dysregulated in mice with combined hyperlipidemia and hyperglycemia than in the hyperlipidemia-only group. The HGHCi-associated genes were related to pathways regulating inflammation (increased Cd68, iNos, and Tnfa expression) and extracellular matrix degradation (Adamts4 and Mmp14). When comparing HFD with PD, the PD aggravated atherosclerosis to a greater extent in mice and showed plaque formation after 8 weeks. Hyperlipidemic and hyperglycemic mice fed a PD (HGHCi PD) showed less collagen (Sirius red) and increased inflammation (CD68-positive cells) within aortic plaques than hyperlipidemic mice (HCi PD). HGHCi-PD mice represent a directly inducible hyperglycemic atherosclerosis model compared with HFD-fed mice, in which atherosclerosis is severe by 8 weeks.

ConclusionWe established a nongenetically inducible mouse model allowing comparative analyses of atherosclerosis in HCi and HGHCi conditions and its modification by diet, allowing analyses of multiple metabolic hits in mice. Improved AlphaFold modeling with implicit experimental information Machine learning prediction algorithms such as AlphaFold1 and RoseTTAFold2 can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy3-6. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation. High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. Decoding the porcine developing spatial processing system and production of human entorhinal stellate cell-like cells by a direct programming approach. Classic studies investigating how and when the entorhinal cortex (component of the memory processing system of the brain) develops have been based on traditional thymidine autoradiography and histological techniques. In this study, we take advantage of modern technologies to trace at a high resolution, the cellular complexity of the developing porcine medial entorhinal cortex by using single-cell profiling. The postnatal medial entorhinal cortex comprises 4 interneuron, 3 pyramidal neuron and 2 stellate cell populations which emerge from intermediate progenitor and immature neuron populations. We discover four MGE-derived interneurons and one CGE-derived interneuron population as well as several IN progenitors. We also identify two oligodendrocyte progenitor populations and three populations of oligodendrocytes. We perform a proof-of-concept experiment demonstrating that porcine scRNA-seq data can be used to develop novel protocols for producing human entorhinal cells in-vitro. We identified six transcription factors (RUNX1A1, SOX5, FOXP1, MEF2C, TCF4, EYA2) important in neurodevelopment and differentiation from one RELN+ stellate cell population. Using a lentiviral vector approach, we reprogrammed human induced pluripotent stem cells into stellate cell-like cells which expressed RELN, SATB2, LEF1 and BCL11B. Our findings contribute to the understanding of the formation of the brains cognitive memory and spatial processing system and provides proof-of-concept for the production of entorhinal cells from human pluripotent stem cells in-vitro. Regulatory perturbations of ribosome allocation optimize the growth proteome with a trade-off in adaptation capacity Bacteria regulate their cellular resource allocation to enable fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth and expression profiles of two sets of fast-growing mutants of Escherichia coli K-12 MG1655 in glucose minimal medium. Mutants with only 3 of the seven copies of ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied rpoB mutants. Higher growth rates due to increased ribosome content affected resource allocation. Expression profiles of fast-growing mutants shared downregulation of hedging functions and upregulated growth functions. Mutants showed longer diauxic shifts and reduced activity of gluconeogenic promoters during glucose-acetate shifts, suggesting reduced availability of the RNA Polymerase for expressing hedging proteome. These results show that the regulation of ribosomal allocation underlies the growth/hedging phenotypes obtained from laboratory evolution experiments. We show how two different regulatory perturbations (rRNA promoters or rpoB mutations) reshape the proteome for growth with a concomitant fitness cost

HighlightsMutants with only 3 ribosomal operons grow faster than wild-type in minimal medium

 {Delta}4 rrn and rpoB mutants share phenotypic traits

Faster growth of mutants is achieved by increased ribosome content

Fast-growing mutants display reduced hedging expression and adaptation trade-offs

Despite similar ribosomal content in rich medium the mutants present growth defects ALLOPURINOL BLOCKS THE AORTIC ANEURYSM IN A MOUSE MODEL OF MARFAN SYNDROME VIA REDUCING AORTIC OXIDATIVE STRESS BackgroundThe pathogenesis and progression of aortic aneurysm in Marfan syndrome (MFS) involves dysregulated TGF-{beta} and nitric oxide signaling, altered hemodynamics, and biomechanical forces. Increasing evidence indicates that redox stress participates in MFS aortopathy, though its contribution is not well established. We reported elevated reactive oxygen species (ROS) formation and NADPH oxidase NOX4 upregulation in MFS patients and mice aortic samples. Here we address the contribution of xanthine oxidoreductase (XOR), which is transcribed as dehydrogenase (XDH) and then post-translationally modified to oxidase (XO), catabolizing mainly purines into uric acid and ROS.

Methods and ResultsWe report that in MFS patients, XOR protein levels increased in aortic samples. In MFS mice (Fbn1C1041G/+), XOR mRNA transcripts augmented in the aorta of young but not older MFS mice. Moreover, the enzymatic activity of XO form increased with respect to XDH. The administration of the XOR inhibitor allopurinol (ALO) blocked the progression of aortic root aneurysm in MFS mice. ALO was also protective when administrated before the appearance of aneurysm. MFS-induced elastic fiber fragmentation, fibrotic remodeling, nuclear translocation of pNRF2, and increased 3-nitrotyrosine levels in the aortic tunica media as well as endothelial dysfunction were all prevented by allopurinol. The large overproduction of H2O2 in MFS aorta did not occur in allopurinol-treated mice whose uric acid plasma levels remained unaltered.

ConclusionsThis study strengthens the concept that redox stress is an important determinant of aortic aneurysm formation and progression in MFS and supports a clinical trial for ALO in the pharmacological treatment of MFS aortopathy.

GRAPHICAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/464182v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@eab02aorg.highwire.dtl.DTLVardef@1d3b39eorg.highwire.dtl.DTLVardef@1b54d0forg.highwire.dtl.DTLVardef@1d61ad0_HPS_FORMAT_FIGEXP  M_FIG C_FIG 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. First detection of herpesvirus and frequency of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. Improving Martini 3 for disordered and multidomain proteins Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small angle X-ray scattering (SAXS) data, and that increasing the strength of protein-water interactions favours more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multi-domain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins. One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction Machine learning (ML) is a key technology to enable accurate prediction of antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two orthogonal problems hinder the current application of ML to antibody-specificity prediction and the benchmarking thereof: (i) The lack of a unified formalized mapping of immunological antibody specificity prediction problems into ML notation and (ii) the unavailability of large-scale training datasets. Here, we developed the Absolut! software suite that allows the parameter-based unconstrained generation of synthetic lattice-based 3D-antibody-antigen binding structures with ground-truth access to conformational paratope, epitope, and affinity. We show that Absolut!-generated datasets recapitulate critical biological sequence and structural features that render antibody-antigen binding prediction challenging. To demonstrate the immediate, high-throughput, and large-scale applicability of Absolut!, we have created an online database of 1 billion antibody-antigen structures, the extension of which is only constrained by moderate computational resources. We translated immunological antibody specificity prediction problems into ML tasks and used our database to investigate paratope-epitope binding prediction accuracy as a function of structural information encoding, dataset size, and ML method, which is unfeasible with existing experimental data. Furthermore, we found that in silico investigated conditions, predicted to increase antibody specificity prediction accuracy, align with and extend conclusions drawn from experimental antibody-antigen structural data. In summary, the Absolut! framework enables the development and benchmarking of ML strategies for biotherapeutics discovery and design.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/451258v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@14295d2org.highwire.dtl.DTLVardef@7a12bdorg.highwire.dtl.DTLVardef@647102org.highwire.dtl.DTLVardef@375112_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical abstractC_FLOATNO The software framework Absolut! enables (A,B) the generation of virtually arbitrarily large numbers of in silico 3D-antibody-antigen structures, (C,D) the formalization of antibody specificity as machine learning (ML) tasks as well as the exploration of ML strategies for paratope-epitope prediction.

C_FIG Highlights- Software framework Absolut! to generate an arbitrarily large number of in silico 3D-antibody-antigen structures
- Generation of one billion in silico antigen-antibody structures reflecting biological layers of complexity that make ML predictions challenging
- Immunological antibody specificity prediction problems formalized as machine learning tasks for which the in silico complexes are immediately usable as benchmark.
- Exploration of machine learning architectures for paratope-epitope interaction prediction accuracy as a function of neural network depth, dataset size, and sequence-structure encoding Phylogenetic analysis of molecular pathways in Tregs Suppressor Function Treg-mediated suppression of conventional T cells is a fundamental step in regulating the adaptive immune response. It is known that Treg first appeared in vertebrates. However, little is known about the of major suppression pathways mediated by Tregs. We employed artificial intelligence text mining system to highlight the suppression pathways currently known to be utilized by Tregs. Our system identified various pathways mediated by CTLA4, calcium signaling, NfkB and NFAT. We simultaneously employed detailed phylogenetic analysis including multiple sequence alignment, phylogenetic tree building, ancestral sequence reconstruction, neutrality tests and positive selection test to investigate the evolution of Treg mediated pathways. We found that CTLA4 first appeared in vertebrates possibly arising from an IGV containing protein in cartilaginous fish. Conversely, we found that Tregs repurposed ancient pathways such as Calcineurin and CAMP Response Element Modulator. Interestingly, these two pathways were highly conserved between vertebrates and lower invertebrates indicating conservation of function. Taken together, our research indicate that Tregs developed its regulatory systems through evolution in vertebrates as well as reusing conserved ancient regulatory systems that are related to the innate immune system. Testing for phylogenetic signal in single-cell RNA-seq data AO_SCPLOWBSTRACTC_SCPLOWPhylogenetic methods are emerging as a useful tool to understand cancer evolutionary dynamics, including tumor structure, heterogeneity, and progression. Most currently used approaches utilize either bulk whole genome sequencing (WGS) or single-cell DNA sequencing (scDNA-seq) and are based on calling copy number alterations and single nucleotide variants (SNVs). Here we explore the potential of single-cell RNA sequencing (scRNA-seq) to reconstruct cancer evolutionary dynamics. scRNA-seq is commonly applied to explore differential gene expression of cancer cells throughout tumor progression. The method exacerbates the single-cell sequencing problem of low yield per cell with uneven expression levels. This accounts for low and uneven sequencing coverage and makes SNV detection and phylogenetic analysis challenging. In this paper, we demonstrate for the first time that scRNA-seq data contains sufficient evolutionary signal and can be utilized in phylogenetic analyses. We explore and compare results of such analyses based on both expression levels and SNVs called from scRNA-seq data. Both techniques are shown to be useful for reconstructing phylogenetic relationships between cells, reflecting the clonal composition of a tumor. Both standardized expression values and SNVs appear to be equally capable of reconstructing a similar pattern of phylogenetic relationship. This pattern is stable even when phylogenetic uncertainty is taken in account. Our results open up a new direction of somatic phylogenetics based on scRNA-seq data. Further research is required to refine and improve these approaches to capture the full picture of somatic evolutionary dynamics in cancer. Outcome-selective reinstatement is predominantly context-independent, and associated with c-Fos activation in the posterior dorsomedial striatum Research from human and animal studies has found that responding that has been successfully reduced following treatment can return upon exposure to certain contexts. An individual in recovery from alcohol use disorder, for example, might relapse to drinking upon visiting their favourite bar. However, most of these data have been derived from experiments involving a single (active) response, and the context-dependence of returned responding in situations involving choice between multiple actions and outcomes is less well-understood. We thus investigated how outcome-selective reinstatement - a procedure involving choice between multiple actions - was affected by altering the physical context in rats. In Experiment 1, rats were trained over 6 days to press a left lever for one food outcome (pellets or sucrose) and a right lever for the other outcome. Then, rats received an extinction session in either the same context (A) as lever press training, or in a different context (B). Rats were tested immediately (5 minutes) after extinction in Context A or B such that there were four groups in total: AAA, ABB, ABA, and AAB. Reinstatement testing consisted of one food outcome being delivered  freely (i.e. unearned by lever pressing and unsignalled by cues) to the food magazine every 4 minutes in the following order: Sucrose, Pellet, Pellet, Sucrose. Selective reinstatement was considered intact if pellet delivery increased pressing selectively on the pellet lever, and sucrose delivery selectively increased pressing on the sucrose lever. This result (Reinstated > Nonreinstated) was observed for rats in group AAA and ABB, but not rats in groups ABA and AAB. Experiment 2 was conducted identically, except that rats received two extinction sessions over two days and tested one day later. This time, all groups demonstrated intact outcome-selective reinstatement regardless of context. Analysis of c-Fos expression in several brain regions revealed that only c-Fos expression in the posterior dorsomedial striatum (pDMS) was related to intact reinstatement performance. Overall, these results suggest that outcome-selective reinstatement is predominantly context-independent, and that intact reinstatement is related to neuronal activity in the pDMS.

HighlightsO_LIOutcome-selective reinstatement is predominantly context-independent
C_LIO_LIOutcome-selective reinstatement is entirely context-independent after multiple extinction sessions
C_LIO_LIOutcome-selective reinstatement increases c-Fos expression in dorsomedial striatum
C_LIO_LIc-Fos expression in orbitofrontal cortex and dorsal hippocampus is unaffected by selective reinstatement.
C_LI 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.

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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 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. Parallel processing in speech perception with local and global representations of linguistic context Speech processing is highly incremental. It is widely accepted that human listeners continuously use the linguistic context to anticipate upcoming concepts, words, and phonemes. However, previous evidence supports two seemingly contradictory models of how a predictive context is integrated with the bottom-up sensory input: Classic psycholinguistic paradigms suggest a two-stage process, in which acoustic input initially leads to local, context-independent representations, which are then quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single coherent, unified interpretation of the input, which fully integrates available information across representational hierarchies, and thus uses contextual constraints to modulate even the earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of local and unified predictive models. Results provide evidence that listeners employ both types of models in parallel. Two local context models uniquely predict some part of early neural responses, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone; at the same time, even early responses to phonemes also reflect a unified model that incorporates sentence level constraints to predict upcoming phonemes. Neural source localization places the anatomical origins of the different predictive models in non-identical parts of the superior temporal lobes bilaterally, with the right hemisphere showing a relative preference for more local models. These results suggest that speech processing recruits both local and unified predictive models in parallel, reconciling previous disparate findings. Parallel models might make the perceptual system more robust, facilitate processing of unexpected inputs, and serve a function in language acquisition.

Impact statementSpeech processing engages multiple predictive models, using sublexical, word- and sentence contexts in parallel to anticipate upcoming phonemes. Salmonella Typhimurium outer membrane protein A (OmpA) renders protection against nitrosative stress by promoting SCV stability in murine macrophages Porins are highly conserved bacterial outer membrane proteins involved in the selective transport of charged molecules across the membrane. Despite their significant contributions to the pathogenesis of Gram-negative bacteria, their precise role in salmonellosis remains elusive. In this study, we investigated the role of porins (OmpA, OmpC, OmpD, and OmpF) in Salmonella Typhimurium (STM) pathogenesis. OmpA played a multifaceted role in STM pathogenesis, and a strain deleted for ompA (STM{Delta} ompA) showed enhanced proneness to phagocytosis and compromised proliferation in macrophages. However, in the epithelial cells, despite being invasion deficient, it was hyper-proliferative. The poor colocalization of STM{Delta} ompA with LAMP-1 confirmed impaired stability of SCV membrane around the intracellular bacteria, resulting in its (STM{Delta} ompA) release into the cytosol of macrophages where it is assaulted with reactive nitrogen intermediates (RNI). The cytosolic localization of STM{Delta} ompA was responsible for the downregulation of SPI-2 encoded virulence factor SpiC, which is required to suppress the activity of iNOS. The reduced recruitment of nitrotyrosine on STM in the macrophage cytosol upon ectopically expressing Listeriolysin O (LLO) explicitly supported the pro-bacterial role of OmpA against the host nitrosative stress. Further, we show that the generation of time-dependent redox burst could be responsible for the enhanced sensitivity of STM{Delta} ompA towards nitrosative stress. The absence of OmpA in STM{Delta} ompA resulted in the loss of integrity and enhanced porosity of the bacterial outer membrane, which was attributed to the upregulated expression of ompC, ompD, and ompF. We showed the involvement of OmpF in the entry of excess nitrite in STM{Delta} ompA, thus increasing the susceptibility of the bacteria towards in vitro and in vivo nitrosative stress. In conclusion, we illustrated a mechanism of strategic utilization of OmpA compared to other porins by wildtype Salmonella for combating the nitrosative stress in macrophages.