Transforming growth factor–β1 (TGF-β1) is one of very few cytokines produced in a latent form, requiring activation to exert any of its vastly diverse effects on development, immunity, and cancer. Regulatory T cells (Tregs) suppress immune cells within close proximity by activating latent TGF-β1 presented by GARP (glycoprotein A repetitions predominant) to integrin αVβ8 on their surface. We solved the crystal structure of GARP:latent TGF-β1 bound to an antibody that stabilizes the complex and blocks release of active TGF-β1. This finding reveals how GARP exploits an unusual medley of interactions, including fold complementation by the amino terminus of TGF-β1, to chaperone and orient the cytokine for binding and activation by αVβ8. Thus, this work further elucidates the mechanism of antibody-mediated blockade of TGF-β1 activation and immunosuppression by Tregs.

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Introduction Mass spectrometry-based proteomics is actively embracing quantitative, singlecell level analyses. Indeed, recent advances in sample preparation and mass spectrometry (MS) have enabled the emergence of quantitative MS-based single-cell proteomics (SCP). While exciting and promising, SCP still has many rough edges. The current analysis workflows are custom and built from scratch. The field is therefore craving for standardized software that promotes principled and reproducible SCP data analyses.Areas covered This special report is the first step toward the formalization and standardization of SCP data analysis. scp, the software that accompanies this work, successfully replicates one of the landmark SCP studies and is applicable to other experiments and designs.We created a repository containing the replicated workflow with comprehensive documentation in order to favor further dissemination and improvements of SCP data analyses. Expert opinionReplicating SCP data analyses uncovers important challenges in SCP data analysis. We describe two such challenges in detail: batch correction and data missingness. We provide the current state-of-the-art and illustrate the associated limitations. We also highlight the intimate dependence that exists between batch effects and data missingness and offer avenues for dealing with these exciting challenges.

1. To locate mating partners and essential resources such as food, oviposition sites and shelter, insects rely to a large extent on chemical cues. While most research has focused on cues derived from plants and insects, there is mounting evidence that indicates that micro-organisms emit volatile compounds that may play an important role in insect behaviour.2. In this study, we assessed how volatile compounds emitted by phylogenetically diverse bacteria affected the olfactory response of the primary parasitoid Aphidius colemani and one of its secondary parasitoids, Dendrocerus aphidum. Olfactory responses were evaluated for volatile blends emitted by bacteria isolated from diverse sources from the parasitoid's habitat, including aphids, aphid mummies and honeydew, and from the parasitoids themselves.3. Results revealed that A. colemani showed a wide variation in response to bacterial volatiles, ranging from significant attraction over no response to significant repellence. Our results further showed that the olfactory response of A. colemani to bacterial volatile emissions was different from that of D. aphidum. Gas chromatography-mass spectrometry analysis of the volatile blends revealed that bacterial strains repellent to A. colemani produced significantly higher amounts of esters, organic acids, aromatics and cycloalkanes than attractive strains. Strains repellent to D. aphidum produced significantly higher amounts of alcohols and ketones, whereas the strains attractive to D. aphidum produced higher amounts of the monoterpenes limonene, linalool and geraniol. 4. Overall, our results indicate that bacterial volatiles can have an important impact on insect olfactory responses, and should therefore be considered as an additional, so far often overlooked factor in studying multitrophic interactions between plants and insects. K E Y W O R D SAphidius colemani, chemical communication, Dendrocerus aphidum, microbial odour, multitrophic interactions, natural enemy, semiochemical, VOCs | 509 Functional Ecology GOELEN Et aL. Islam S. Sobhy https://orcid.org/0000-0003-4984-1823 Jetske G. de Boer https://orcid.org/0000-0002-3182-8543 Kevin J. Verstrepen https://orcid.org/0000-0002-3077-6219 Hans Jacquemyn https://orcid.org/0000-0001-9600-5794 Bart Lievens https://orcid.org/0000-0002-7698-6641 S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Goelen T, Sobhy IS, Vanderaa C, et al. Volatiles of bacteria associated with parasitoid habitats elicit distinct olfactory responses in an aphid parasitoid and its hyperparasitoid. Funct Ecol. 2020;34:507-520. https ://doi.

Sound data analysis is essential to retrieve meaningful biological information from single‐cell proteomics experiments. This analysis is carried out by computational methods that are assembled into workflows, and their implementations influence the conclusions that can be drawn from the data. In this work, we explore and compare the computational workflows that have been used over the last four years and identify a profound lack of consensus on how to analyze single‐cell proteomics data. We highlight the need for benchmarking of computational workflows and standardization of computational tools and data, as well as carefully designed experiments. Finally, we cover the current standardization efforts that aim to fill the gap, list the remaining missing pieces, and conclude with lessons learned from the replication of published single‐cell proteomics analyses. © 2023 Wiley Periodicals LLC.

There is increasing evidence that microorganisms emit a wide range of volatile compounds (mVOCs, microbial volatile organic compounds) that act as insect semiochemicals, and therefore play an important role in insect behaviour. Although it is generally believed that phylogenetically closely related microbes tend to have similar phenotypic characteristics and therefore may elicit similar responses in insects, currently little is known about whether the evolutionary history and phylogenetic relationships among microorganisms have an impact on insect–microbe interactions. In this study, we tested the hypothesis that phylogenetic relationships among 40 Bacillus strains isolated from diverse environmental sources predicted mVOC composition and the olfactory response of the generalist aphid parasitoid Aphidius colemani. Results revealed that phylogenetically closely related Bacillus strains emitted similar blends of mVOCs and elicited a comparable olfactory response of A. colemani in Y‐tube olfactometer bioassays, varying between attraction and repellence. Analysis of the chemical composition of the mVOC blends showed that all Bacillus strains produced a highly similar set of volatiles, but often in different concentrations and ratios. Benzaldehyde was produced in relatively high concentrations by strains that repel A. colemani, while attractive mVOC blends contained relatively higher amounts of acetoin, 2,3‐butanediol, 2,3‐butanedione, eucalyptol and isoamylamine. Overall, these results indicate that bacterial phylogeny had a strong impact on mVOC compositions and as a result on the olfactory responses of insects.

Mass spectrometry-based proteomics is actively embracing quantitative, single cell-level analyses. Indeed, recent advances in sample preparation and mass spectrometry (MS) have enabled the emergence of quantitative MS-based single-cell proteomics (SCP). While exciting and promising, SCP still has many rough edges. The current analysis workflows are custom and build from scratch. The field is therefore craving for standardized software that promotes principled and reproducible SCP data analyses. This special report represents the first step toward the formalization of standard SCP data analysis. scp, the software that accompanies this work can successfully reproduces one of the landmark data in the field of SCP. We created a repository containing the reproduction workflow with comprehensive documentation in order to favor further dissemination and improvement of SCP data analyses.Reproducing SCP data analyses uncovers important challenges in SCP data analysis. We describe two such challenges in detail: batch correction and data missingness. We provide the current state-of-the-art and illustrate the associated limitations. We also highlights the intimate dependence that exists between batch effects and data missingness and provides future tracks for dealing with these exciting challenges.

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