ER chaperones use a protein folding and quality control glyco-code.

N-glycans act as quality control tags by recruiting lectin chaperones to assist protein maturation in the endoplasmic reticulum. The location and composition of N-glycans (glyco-code) are key to the chaperone-selection process. Serpins, a class of serine protease inhibitors, fold non-sequentially to achieve metastable active states. Here, the role of the glyco-code in assuring successful maturation and quality control of two human serpins, alpha-1 antitrypsin (AAT) and antithrombin III (ATIII), is described. We find that AAT, which has glycans near its N terminus, is assisted by early lectin chaperone binding. In contrast, ATIII, which has more C-terminal glycans, is initially helped by BiP and then later by lectin chaperones mediated by UGGT reglucosylation. UGGT action is increased for misfolding-prone disease variants, and these clients are preferentially glucosylated on their most C-terminal glycan. Our study illustrates how serpins utilize N-glycan presence, position, and composition to direct their proper folding, quality control, and trafficking.

An ADP-ribosyltransferase toxin kills bacterial cells by modifying structured non-coding RNAs.

ADP-ribosyltransferases (ARTs) were among the first identified bacterial virulence factors. Canonical ART toxins are delivered into host cells where they modify essential proteins, thereby inactivating cellular processes and promoting pathogenesis. Our understanding of ARTs has since expanded beyond protein-targeting toxins to include antibiotic inactivation and DNA damage repair. Here, we report the discovery of RhsP2 as an ART toxin delivered between competing bacteria by a type VI secretion system of Pseudomonas aeruginosa. A structure of RhsP2 reveals that it resembles protein-targeting ARTs such as diphtheria toxin. Remarkably, however, RhsP2 ADP-ribosylates 2'-hydroxyl groups of double-stranded RNA, and thus, its activity is highly promiscuous with identified cellular targets including the tRNA pool and the RNA-processing ribozyme, ribonuclease P. Consequently, cell death arises from the inhibition of translation and disruption of tRNA processing. Overall, our data demonstrate a previously undescribed mechanism of bacterial antagonism and uncover an unprecedented activity catalyzed by ART enzymes.

Tuning sterol extraction kinetics yields a renal-sparing polyene antifungal.

Decades of previous efforts to develop renal-sparing polyene antifungals were misguided by the classic membrane permeabilization model1. Recently, the clinically vital but also highly renal-toxic small-molecule natural product amphotericin B was instead found to kill fungi primarily by forming extramembraneous sponge-like aggregates that extract ergosterol from lipid bilayers2-6. Here we show that rapid and selective extraction of fungal ergosterol can yield potent and renal-sparing polyene antifungals. Cholesterol extraction was found to drive the toxicity of amphotericin B to human renal cells. Our examination of high-resolution structures of amphotericin B sponges in sterol-free and sterol-bound states guided us to a promising structural derivative that does not bind cholesterol and is thus renal sparing. This derivative was also less potent because it extracts ergosterol more slowly. Selective acceleration of ergosterol extraction with a second structural modification yielded a new polyene, AM-2-19, that is renal sparing in mice and primary human renal cells, potent against hundreds of pathogenic fungal strains, resistance evasive following serial passage in vitro and highly efficacious in animal models of invasive fungal infections. Thus, rational tuning of the dynamics of interactions between small molecules may lead to better treatments for fungal infections that still kill millions of people annually7,8 and potentially other resistance-evasive antimicrobials, including those that have recently been shown to operate through supramolecular structures that target specific lipids9.

Excitons and emergent quantum phenomena in stacked 2D semiconductors.

The design and control of material interfaces is a foundational approach to realize technologically useful effects and engineer material properties. This is especially true for two-dimensional (2D) materials, where van der Waals stacking allows disparate materials to be freely stacked together to form highly customizable interfaces. This has underpinned a recent wave of discoveries based on excitons in stacked double layers of transition metal dichalcogenides (TMDs), the archetypal family of 2D semiconductors. In such double-layer structures, the elegant interplay of charge, spin and moiré superlattice structure with many-body effects gives rise to diverse excitonic phenomena and correlated physics. Here we review some of the recent discoveries that highlight the versatility of TMD double layers to explore quantum optics and many-body effects. We identify outstanding challenges in the field and present a roadmap for unlocking the full potential of excitonic physics in TMD double layers and beyond, such as incorporating newly discovered ferroelectric and magnetic materials to engineer symmetries and add a new level of control to these remarkable engineered materials.

Presymptomatic training mitigates functional deficits in a mouse model of Rett syndrome.

Mutations in the X-linked gene MECP2 cause Rett syndrome, a progressive neurological disorder in which children develop normally for the first one or two years of life before experiencing profound motor and cognitive decline1-3. At present there are no effective treatments for Rett syndrome, but we hypothesized that using the period of normal development to strengthen motor and memory skills might confer some benefit. Here we find, using a mouse model of Rett syndrome, that intensive training beginning in the presymptomatic period dramatically improves the performance of specific motor and memory tasks, and significantly delays the onset of symptoms. These benefits are not observed when the training begins after symptom onset. Markers of neuronal activity and chemogenetic manipulation reveal that task-specific neurons that are repeatedly activated during training develop more dendritic arbors and have better neurophysiological responses than those in untrained animals, thereby enhancing their functionality and delaying symptom onset. These results provide a rationale for genetic screening of newborns for Rett syndrome, as presymptomatic intervention might mitigate symptoms or delay their onset. Similar strategies should be studied for other childhood neurological disorders.

A tandem activity-based sensing and labeling strategy reveals antioxidant response element regulation of labile iron pools.

Iron is an essential element for life owing to its ability to participate in a diverse array of oxidation-reduction reactions. However, misregulation of iron-dependent redox cycling can also produce oxidative stress, contributing to cell growth, proliferation, and death pathways underlying aging, cancer, neurodegeneration, and metabolic diseases. Fluorescent probes that selectively monitor loosely bound Fe(II) ions, termed the labile iron pool, are potentially powerful tools for studies of this metal nutrient; however, the dynamic spatiotemporal nature and potent fluorescence quenching capacity of these bioavailable metal stores pose challenges for their detection. Here, we report a tandem activity-based sensing and labeling strategy that enables imaging of labile iron pools in live cells through enhancement in cellular retention. Iron green-1 fluoromethyl (IG1-FM) reacts selectively with Fe(II) using an endoperoxide trigger to release a quinone methide dye for subsequent attachment to proximal biological nucleophiles, providing a permanent fluorescent stain at sites of elevated labile iron. IG1-FM imaging reveals that degradation of the major iron storage protein ferritin through ferritinophagy expands the labile iron pool, while activation of nuclear factor-erythroid 2-related factor 2 (NRF2) antioxidant response elements (AREs) depletes it. We further show that lung cancer cells with heightened NRF2 activation, and thus lower basal labile iron, have reduced viability when treated with an iron chelator. By connecting labile iron pools and NRF2-ARE activity to a druggable metal-dependent vulnerability in cancer, this work provides a starting point for broader investigations into the roles of transition metal and antioxidant signaling pathways in health and disease.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes.

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Novel antifungals and treatment approaches to tackle resistance and improve outcomes of invasive fungal disease.

SUMMARYFungal infections are on the rise, driven by a growing population at risk and climate change. Currently available antifungals include only five classes, and their utility and efficacy in antifungal treatment are limited by one or more of innate or acquired resistance in some fungi, poor penetration into "sequestered" sites, and agent-specific side effect which require frequent patient reassessment and monitoring. Agents with novel mechanisms, favorable pharmacokinetic (PK) profiles including good oral bioavailability, and fungicidal mechanism(s) are urgently needed. Here, we provide a comprehensive review of novel antifungal agents, with both improved known mechanisms of actions and new antifungal classes, currently in clinical development for treating invasive yeast, mold (filamentous fungi), Pneumocystis jirovecii infections, and dimorphic fungi (endemic mycoses). We further focus on inhaled antifungals and the role of immunotherapy in tackling fungal infections, and the specific PK/pharmacodynamic profiles, tissue distributions as well as drug-drug interactions of novel antifungals. Finally, we review antifungal resistance mechanisms, the role of use of antifungal pesticides in agriculture as drivers of drug resistance, and detail detection methods for antifungal resistance.

Central nervous system status is prognostic in T-cell acute lymphoblastic leukemia: a Children's Oncology Group report.

To determine the prognostic significance of central nervous system (CNS) leukemic involvement in newly diagnosed T-cell acute lymphoblastic leukemia (T-ALL), outcomes on consecutive, phase 3 Children's Oncology Group clinical trials were examined. AALL0434 and AALL1231 tested efficacy of novel agents within augmented-Berlin-Frankfurt-Münster (aBFM) therapy. In addition to testing study-specific chemotherapy through randomization, the AALL0434 regimen delivered cranial radiation therapy (CRT) to most participants (90.8%), whereas AALL1231 intensified chemotherapy to eliminate CRT in 88.2% of participants. In an analysis of 2164 patients with T-ALL (AALL0434, 1550; AALL1231, 614), 1564 had CNS-1 (72.3%), 441 CNS-2 (20.4%), and 159 CNS-3 (7.3%). The 4-year event-free-survival (EFS) was similar for CNS-1 (85.1% ± 1.0%) and CNS-2 (83.2% ± 2.0%), but lower for CNS-3 (71.8% ± 4.0%; P = .0004). Patients with CNS-1 and CNS-2 had similar 4-year overall survival (OS) (90.1% ± 0.8% and 90.5% ± 1.5%, respectively), with OS for CNS-3 being 82.7% ± 3.4% (P = .005). Despite therapeutic differences, outcomes for CNS-1 and CNS-2 were similar regardless of CRT, intensified corticosteroids, or novel agents. Except for significantly superior outcomes with nelarabine on AALL0434 (4-year disease-free survival, 93.1% ± 5.2%), EFS/OS was inferior with CNS-3 status, all of whom received CRT. Combined analyses of >2000 patients with T-ALL identified that CNS-1 and CNS-2 status at diagnosis had similar outcomes. Unlike B-ALL, CNS-2 status in T-ALL does not impact outcome with aBFM therapy, without additional intrathecal therapy, with or without CRT. Although nelarabine improved outcomes for those with CNS-3 status, novel approaches are needed. These trials were registered at www.clinicaltrials.gov as #NCT00408005 (AALL0434) and #NCT02112916 (AALL1231).

Clinical Potential of Adrenomedullin Signaling in the Cardiovascular System.

Numerous clinical studies have revealed the utility of circulating AM (adrenomedullin) or MR-proAM (mid-regional proAM 45-92) as an effective prognostic and diagnostic biomarker for a variety of cardiovascular-related pathophysiologies. Thus, there is strong supporting evidence encouraging the exploration of the AM-CLR (calcitonin receptor-like receptor) signaling pathway as a therapeutic target. This is further bolstered because several drugs targeting the shared CGRP (calcitonin gene-related peptide)-CLR pathway are already Food and Drug Administration-approved and on the market for the treatment of migraine. In this review, we summarize the AM-CLR signaling pathway and its modulatory mechanisms and provide an overview of the current understanding of the physiological and pathological roles of AM-CLR signaling and the yet untapped potentials of AM as a biomarker or therapeutic target in cardiac and vascular diseases and provide an outlook on the recently emerged strategies that may provide further boost to the possible clinical applications of AM signaling.

Signatures of moiré-trapped valley excitons in MoSe2/WSe2 heterobilayers.

The formation of moiré patterns in crystalline solids can be used to manipulate their electronic properties, which are fundamentally influenced by periodic potential landscapes. In two-dimensional materials, a moiré pattern with a superlattice potential can be formed by vertically stacking two layered materials with a twist and/or a difference in lattice constant. This approach has led to electronic phenomena including the fractal quantum Hall effect1-3, tunable Mott insulators4,5 and unconventional superconductivity6. In addition, theory predicts that notable effects on optical excitations could result from a moiré potential in two-dimensional valley semiconductors7-9, but these signatures have not been detected experimentally. Here we report experimental evidence of interlayer valley excitons trapped in a moiré potential in molybdenum diselenide (MoSe2)/tungsten diselenide (WSe2) heterobilayers. At low temperatures, we observe photoluminescence close to the free interlayer exciton energy but with linewidths over one hundred times narrower (around 100 microelectronvolts). The emitter g-factors are homogeneous across the same sample and take only two values, -15.9 and 6.7, in samples with approximate twist angles of 60 degrees and 0 degrees, respectively. The g-factors match those of the free interlayer exciton, which is determined by one of two possible valley-pairing configurations. At twist angles of approximately 20 degrees the emitters become two orders of magnitude dimmer; however, they possess the same g-factor as the heterobilayer at a twist angle of approximately 60 degrees. This is consistent with the umklapp recombination of interlayer excitons near the commensurate 21.8-degree twist angle7. The emitters exhibit strong circular polarization of the same helicity for a given twist angle, which suggests that the trapping potential retains three-fold rotational symmetry. Together with a characteristic dependence on power and excitation energy, these results suggest that the origin of the observed effects is interlayer excitons trapped in a smooth moiré potential with inherited valley-contrasting physics. This work presents opportunities to control two-dimensional moiré optics through variation of the twist angle.

Visualizing electrostatic gating effects in two-dimensional heterostructures.

The ability to directly monitor the states of electrons in modern field-effect devices-for example, imaging local changes in the electrical potential, Fermi level and band structure as a gate voltage is applied-could transform our understanding of the physics and function of a device. Here we show that micrometre-scale, angle-resolved photoemission spectroscopy1-3 (microARPES) applied to two-dimensional van der Waals heterostructures4 affords this ability. In two-terminal graphene devices, we observe a shift of the Fermi level across the Dirac point, with no detectable change in the dispersion, as a gate voltage is applied. In two-dimensional semiconductor devices, we see the conduction-band edge appear as electrons accumulate, thereby firmly establishing the energy and momentum of the edge. In the case of monolayer tungsten diselenide, we observe that the bandgap is renormalized downwards by several hundreds of millielectronvolts-approaching the exciton energy-as the electrostatic doping increases. Both optical spectroscopy and microARPES can be carried out on a single device, allowing definitive studies of the relationship between gate-controlled electronic and optical properties. The technique provides a powerful way to study not only fundamental semiconductor physics, but also intriguing phenomena such as topological transitions5 and many-body spectral reconstructions under electrical control.

Benchmarking Bioinformatics Pipelines in Data-Independent Acquisition Mass Spectrometry for Immunopeptidomics.

Immunopeptidomes are the peptide repertoires bound by the molecules encoded by the major histocompatibility complex [human leukocyte antigen (HLA) in humans]. These HLA-peptide complexes are presented on the cell surface for immune T-cell recognition. Immunopeptidomics denotes the utilization of tandem mass spectrometry to identify and quantify peptides bound to HLA molecules. Data-independent acquisition (DIA) has emerged as a powerful strategy for quantitative proteomics and deep proteome-wide identification; however, DIA application to immunopeptidomics analyses has so far seen limited use. Further, of the many DIA data processing tools currently available, there is no consensus in the immunopeptidomics community on the most appropriate pipeline(s) for in-depth and accurate HLA peptide identification. Herein, we benchmarked four commonly used spectral library-based DIA pipelines developed for proteomics applications (Skyline, Spectronaut, DIA-NN, and PEAKS) for their ability to perform immunopeptidome quantification. We validated and assessed the capability of each tool to identify and quantify HLA-bound peptides. Generally, DIA-NN and PEAKS provided higher immunopeptidome coverage with more reproducible results. Skyline and Spectronaut conferred more accurate peptide identification with lower experimental false-positive rates. All tools demonstrated reasonable correlations in quantifying precursors of HLA-bound peptides. Our benchmarking study suggests a combined strategy of applying at least two complementary DIA software tools to achieve the greatest degree of confidence and in-depth coverage of immunopeptidome data.

Environmental outcomes of the US Renewable Fuel Standard.

The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and thereby guides nearly half of all global biofuel production, yet outcomes of this keystone climate and environmental regulation remain unclear. Here we combine econometric analyses, land use observations, and biophysical models to estimate the realized effects of the RFS in aggregate and down to the scale of individual agricultural fields across the United States. We find that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 2.8 Mha (8.7%) and total cropland by 2.1 Mha (2.4%) in the years following policy enactment (2008 to 2016). These changes increased annual nationwide fertilizer use by 3 to 8%, increased water quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision-makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.

Lipopolysaccharide Regulates the Macrophage RNA-Binding Proteome.

RNA-protein interactions within cellular signaling pathways have significant modulatory effects on RNA binding proteins' (RBPs') effector functions. During the innate immune response, specific RNA-protein interactions have been reported as a regulatory layer of post-transcriptional control. We investigated changes in the RNA-bound proteome of immortalized mouse macrophages (IMM) following treatment with lipopolysaccharide (LPS). Stable isotope labeling by amino acids in cell culture (SILAC) of cells followed by unbiased purification of RNP complexes at two time points after LPS stimulation and bottom-up proteomic analysis by LC-MS/MS resulted in a set of significantly affected RBPs. Global RNA sequencing and LFQ proteomics were used to characterize the correlation of transcript and protein abundance changes in response to LPS at different time points with changes in protein-RNA binding. Il1α, MARCKS, and ACOD1 were noted as RBP candidates involved in innate immune signaling. The binding sites of the RBP and RNA conjugates at amino acid resolution were investigated by digesting the cross-linked oligonucleotide from peptides remaining after elution using Nuclease P1. The combined data sets provide directions for further studies of innate immune signaling regulation by RBP interactions with different classes of RNA.

Intrinsically disordered regions that drive phase separation form a robustly distinct protein class.

Protein phase separation is thought to be a primary driving force for the formation of membrane-less organelles, which control a wide range of biological functions from stress response to ribosome biogenesis. Among phase-separating (PS) proteins, many have intrinsically disordered regions (IDRs) that are needed for phase separation to occur. Accurate identification of IDRs that drive phase separation is important for testing the underlying mechanisms of phase separation, identifying biological processes that rely on phase separation, and designing sequences that modulate phase separation. To identify IDRs that drive phase separation, we first curated datasets of folded, ID, and PS ID sequences. We then used these sequence sets to examine how broadly existing amino acid property scales can be used to distinguish between the three classes of protein regions. We found that there are robust property differences between the classes and, consequently, that numerous combinations of amino acid property scales can be used to make robust predictions of protein phase separation. This result indicates that multiple, redundant mechanisms contribute to the formation of phase-separated droplets from IDRs. The top-performing scales were used to further optimize our previously developed predictor of PS IDRs, ParSe. We then modified ParSe to account for interactions between amino acids and obtained reasonable predictive power for mutations that have been designed to test the role of amino acid interactions in driving protein phase separation. Collectively, our findings provide further insight into the classification of IDRs and the elements involved in protein phase separation.

TTC17 is an endoplasmic reticulum resident TPR-containing adaptor protein.

Protein folding, quality control, maturation, and trafficking are essential processes for proper cellular homeostasis. Around one-third of the human proteome is targeted to the endoplasmic reticulum (ER), the organelle that serves as entrance into the secretory pathway. Successful protein trafficking is paramount for proper cellular function and to that end there are many ER resident proteins that ensure efficient secretion. Here, biochemical and cell biological analysis was used to determine that TTC17 is a large, soluble, ER-localized protein that plays an important role in secretory trafficking. Transcriptional analysis identified the predominantly expressed protein isoform of TTC17 in various cell lines. Further, TTC17 localizes to the ER and interacts with a wide variety of chaperones and cochaperones normally associated with ER protein folding, quality control, and maturation processes. TTC17 was found to be significantly upregulated by ER stress and through the creation and use of TTC17-/- cell lines, quantitative mass spectrometry identified secretory pathway wide trafficking defects in the absence of TTC17. Notably, trafficking of insulin-like growth factor type 1 receptor, glycoprotein nonmetastatic melanoma protein B, clusterin, and UDP-glucose:glycoprotein glucosyltransferase 1 were significantly altered in H4 neuroglioma cells. This study defines a novel ER trafficking factor and provides insight into the protein-protein assisted trafficking in the early secretory pathway.

2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces.

The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.

Genetics of flight in spongy moths (Lymantria dispar ssp.): functionally integrated profiling of a complex invasive trait.

BACKGROUND: Flight can drastically enhance dispersal capacity and is a key trait defining the potential of exotic insect species to spread and invade new habitats. The phytophagous European spongy moths (ESM, Lymantria dispar dispar) and Asian spongy moths (ASM; a multi-species group represented here by L. d. asiatica and L. d. japonica), are globally invasive species that vary in adult female flight capability-female ASM are typically flight capable, whereas female ESM are typically flightless. Genetic markers of flight capability would supply a powerful tool for flight profiling of these species at any intercepted life stage. To assess the functional complexity of spongy moth flight and to identify potential markers of flight capability, we used multiple genetic approaches aimed at capturing complementary signals of putative flight-relevant genetic divergence between ESM and ASM: reduced representation genome-wide association studies, whole genome sequence comparisons, and developmental transcriptomics. We then judged the candidacy of flight-associated genes through functional analyses aimed at addressing the proximate demands of flight and salient features of the ecological context of spongy moth flight evolution. RESULTS: Candidate gene sets were typically non-overlapping across different genetic approaches, with only nine gene annotations shared between any pair of approaches. We detected an array of flight-relevant functional themes across gene sets that collectively suggest divergence in flight capability between European and Asian spongy moth lineages has coincided with evolutionary differentiation in multiple aspects of flight development, execution, and surrounding life history. Overall, our results indicate that spongy moth flight evolution has shaped or been influenced by a large and functionally broad network of traits. CONCLUSIONS: Our study identified a suite of flight-associated genes in spongy moths suited to exploration of the genetic architecture and evolution of flight, or validation for flight profiling purposes. This work illustrates how complementary genetic approaches combined with phenotypically targeted functional analyses can help to characterize genetically complex traits.

recolorize: An R package for flexible colour segmentation of biological images.

Colour pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing colour pattern geometries across images requires colour segmentation, where pixels in an image are assigned to one of a set of colour classes shared by all images. Manual methods for colour segmentation are slow and subjective, while automated methods can struggle with high technical variation in aggregate image sets. We present recolorize, an R package toolbox for human-subjective colour segmentation with functions for batch-processing low-variation image sets and additional tools for handling images from diverse (high-variation) sources. The package also includes export options for a variety of formats and colour analysis packages. This paper illustrates recolorize for three example datasets, including high variation, batch processing and combining with reflectance spectra, and demonstrates the downstream use of methods that rely on this output.