Miracle-dz/UniFAR-FTUs huggingface dataset:
SUMO-activated target traps (SATTs) enable the identification of a comprehensive E3-specific SUMO proteome

Ubiquitin and ubiquitin-like conjugation cascades consist of dedicated E1, E2 and E3 enzymes with E3s providing substrate specificity. Mass spectrometry-based approaches have enabled the identification of more than 60,000 acceptor sites for ubiquitin and 40,000 acceptor sites for SUMO2/3. However, E3-to-target wiring is poorly understood. The limited number of SUMO E3s provides the unique opportunity to systematically study E3-substrate wiring. We developed SUMO Activated Target Traps (SATTs) and systematically identified substrates for eight different SUMO E3s, PIAS1, PIAS2, PIAS3, PIAS4, NSMCE2, ZNF451, LAZSUL(ZNF451-3) and ZMIZ2. SATTs enabled us to identify 590 SUMO1 and 1195 SUMO2/3 targets in an E3-specific manner. We found pronounced E3 substrate preference, even at the substrate isoform level. Quantitative proteomics enabled us to measure substrate specificity of E3s, quantified using the SATT index. Furthermore, we developed the Polar SATTs web-based tool (https://amsterdamstudygroup.shinyapps.io/PolaRVolcaNoseR/) to browse the dataset in an interactive manner, increasing the accessibility of this resource for the community. Overall, we uncover E3-to-target wiring of 1681 SUMO substrates, highlighting unique and overlapping sets of substrates for eight different SUMO E3 ligases.
Modeling the rarest of the rare: A comparison between joint species distribution models, ensembles of small models, and single-species models at extremely low sample sizes

Determining the distribution and environmental preferences of rare species threatened by global change has long been a focus of conservation. Typical minimum suggested number of occurrences ranges from ∼5 to 30, but many species are represented by even fewer occurrences. However, several newer methods may be able to accommodate such low samples sizes. These include Bayesian joint species distribution models (JSDMs) which allow rare species to statistically “borrow strength” from more common species with similar niches, and ensembles of small models (ESMs), which reduce the number of parameters by averaging smaller models. Here we explore how niche breadth and niche position relative to other species influence model performance at low sample sizes (N=2, 4, 8, 16, 32, 64) using virtual species within a community of real species. ESMs were better at discrimination tasks for most species, and yielded better-than-random accuracy even for N=2. In contrast, “traditional” single species or JSDMs were better able to estimate the underlying response curves of variables that influenced the niche, but at low sample sizes also were more likely to incorrectly identify unimportant factors as influential. Species with niches that were narrow and peripheral to the available environmental space yielded models with better discrimination capacity than species with broad niches or niches that were similar to those of other species, regardless of whether the modeling algorithm allowed for borrowing of strength. Our study suggests that some rare species may be able to be modeled reliably at very low sample sizes, although the best algorithm depends on number of occurrences and whether the niche or distribution is the focus.
A Novel Widespread MITE Element in the Repeat-Rich Genome of the Cardinium Endosymbiont of the Spider Oedothorax gibbosus

Cardinium bacteria, a widespread symbiont lineage found across insects and nematodes, have been linked to reproductive manipulation of their hosts. However, the study of Cardinium has been hampered by the lack of comprehensive genomic resources. ABSTRACT Free-living bacteria have evolved multiple times to become host-restricted endosymbionts. The transition from a free-living to a host-restricted lifestyle comes with a number of different genomic changes, including a massive loss of genes. In host-restricted endosymbionts, gene inactivation and genome reduction are facilitated by mobile genetic elements, mainly insertion sequences (ISs). ISs are small autonomous mobile elements, and one of, if not the most, abundant transposable elements in bacteria. Proliferation of ISs is common in some facultative endosymbionts, and is likely driven by the transmission bottlenecks, which increase the level of genetic drift. In this study, we present a manually curated genome annotation for a Cardinium endosymbiont of the dwarf spider Oedothorax gibbosus. Cardinium species are host-restricted endosymbionts that, similarly to ColbachiaWolbachia spp. , include strains capable of manipulating host reproduction. Through the focus on mobile elements, the annotation revealed a rampant spread of ISs, extending earlier observations in other Cardinium genomes. We found that a large proportion of IS elements are pseudogenized, with many displaying evidence of recent inactivation. Most notably, we describe the lineage-specific emergence and spread of a novel IS-derived Miniature Inverted repeat Transposable Element (MITE), likely being actively maintained by intact copies of its parental IS982-family element. This study highlights the relevance of manual curation of these repeat-rich endosymbiont genomes for the discovery of novel MITEs, as well as the possible role these understudied elements might play in genome streamlining. IMPORTANCE Cardinium bacteria, a widespread symbiont lineage found across insects and nematodes, have been linked to reproductive manipulation of their hosts. However, the study of Cardinium has been hampered by the lack of comprehensive genomic resources. The high content of mobile genetic elements, namely, insertion sequences (ISs), has long complicated the analyses and proper annotations of these genomes. In this study, we present a manually curated annotation of the Cardinium symbiont of the spider Oedothorax gibbosus. Most notably, we describe a novel IS-like element found exclusively in this strain. We show that this mobile element likely evolved from a defective copy of its parental IS and then spread throughout the genome, contributing to the pseudogenization of several other mobile elements. We propose this element is likely being maintained by the intact copies of its parental IS element and that other similar elements in the genome could potentially follow this route.
Rab7/Retromer-based endolysosomal trafficking facilitates effector secretion and host invasion in rice blast

Secretion is a fundamental process in all living organisms. Using conventional secretion pathways, many plant pathogens release effectors into the host plants to downregulate immunity and promote infection. However, this does not always constitute the only way that effectors are sorted and tracked to their final destination such as the biotrophic interfacial complex-associated effectors produced by the blast fungus Magnaporthe oryzae. Here, we uncover a novel unconventional route originating from fungal vacuolar membrane to the host interface and plasma membrane. We found that a GFP-MoRab7 labeled vacuole is closely associated with the interface structure throughout M. oryzae invasive growth. Conditional inactivation of MoRab7 impaired the establishment of the biotrophy interface and secretion of Pwl2 effector. To perform the vacuolar trafficking pathway, MoRab7 first recruits the retromer complex to the vacuole membrane, enabling it recognizes a batch of SNARE proteins, including the v-SNARE MoSnc1. Live-cell imaging supports both retromer complex component and MoSnc1 protein labeled vesicles showing the trafficking dynamics toward the interface or plasma membrane, and then fusion with target membranes. Lastly, disruption of the MoRab7/Retromer/MoSnc1-based endolysosomal cascade affects effector secretion and fungal pathogenicity. Taken together, we discovered an unconventional protein and membrane trafficking route starting from the fungal endolysosomes to the M. oryzae-rice interaction interface, and dissect the role of MoRab7/Retromer/MoSnc1 constituent sorting machinery in effector secretion during invasive growth in M. oryzae.
Characterization of cell-to-cell variation in nuclear transport rates and identification of its sources

Nuclear transport is an essential part of eukaryotic cell function. Several assays exist to measure the rate of this process, but not at the single-cell level. Here, we developed a fluorescent recovery after photobleaching (FRAP)- based method to determine nuclear import and export rates independently in individual live cells. To overcome the inherent noise of single-cell measurements, we performed sequential FRAPs on the same cell. We found large cell-to-cell variation in transport rates within isogenic yeast populations. Our data suggest that a main determinant of this heterogeneity may be variability in the number of nuclear pore complexes (NPCs). For passive transport, this component explained most of the variability. Actively transported proteins were influenced by variability in additional components, including general factors such as the Ran-GTP gradient as well as specific regulators of the export rate. By considering mother-daughter pairs, we showed that mitotic segregation of the transport machinery is too noisy to control cellular inheritance. Finally, we studied mother-daughter cell asymmetry in the localization of the transcription factor Ace2, which is specifically concentrated in daughter cell nuclei. We found that this asymmetry is the outcome of a higher ratio of import rate to export rate in daughters. Interestingly, rather than reduced export in the daughter cell, as previously hypothesized, rates of both import and export are faster in daughter cells than in mother cells, but the magnitude of increase is greater for import. These results shed light into cell-to-cell variation in cellular dynamics and its sources.
Octopamine affects gustatory responsiveness and associative learning performance in bumble bees

Octopamine has broad roles within invertebrate nervous systems as a neurohormone, neurotransmitter and neuromodulator. It orchestrates foraging behavior in many insect taxa via effects on feeding, gustatory responsiveness and appetitive learning. Knowledge of how this biogenic amine regulates bee physiology and behavior is based largely on study of a single species, the honey bee, Apis mellifera. Until recently, its role in the foraging ecology and social organization of diverse bee taxa had been unexplored. Bumble bees (Bombus spp.) are a model for the study of foraging and learning, and its neural basis, but whether octopamine similarly affects sensory and cognitive performance in this genus is not known. To address this gap, we explored the effects of octopamine on sucrose response thresholds and associative learning in Bombus impatiens via conditioning of the Proboscis Extension Reflex (PER) using a visual (color) cue. We found that octopamine had similar effects on bumble bee behavior as honey bees, however, higher doses were required to induce these effects. At this higher dose, octopamine lowered bees’ sucrose response thresholds and appeared to enhance associative learning performance. Adding to recent studies on stingless bees (Meliponini), these findings support the idea that octopamine’s role in reward processing and learning is broadly conserved across Apidae, while pointing towards some differences across systems worth exploring further.
Self-paced treadmill controller algorithm based on position and speed of centre of mass

Background Self-paced treadmills are increasingly used in clinical and research settings. Using self-paced (SP) treadmills, researchers can simulate overground walking while participants can walk with different but comfortable gait speeds in a controlled environment. Several algorithms have been designed for self-paced treadmills based on data from force plates, motion capture, and even marker-less systems such as 3D depth cameras. Methods We present a non-linear controller that implements a self-paced algorithm integrated with treadmills. This algorithm uses the subject’s centre-of-mass (CoM) position and velocity, relative to the front and back end of the treadmill as inputs. The controller continuously adjusts the treadmill’s belt speed via belt acceleration. The algorithm attempts to prevent the subject reaching the front and back of treadmill via minimal treadmill acceleration. Findings This method has been safely used in previous studies with over 410 subjects in various populations. We simulated the use of the SP algorithm with three different sensitivities (0.2, 1 and 2). The belt speed predicted by algorithm simulation in matched well with the belt speeds of experiments in (Gait Realtime Analysis Interactive Lab (GRAIL) system. Interpretation This algorithm is integrated with a VR environment in which the subject can be immersed and even be mechanically perturbed. Additionally, this algorithm can be implemented in other treadmills where CoM position is known. We encourage researchers to use and build upon our well-established SP algorithm toward a more standardized SP algorithm in different gait scenarios across various instrumented treadmills with different populations.
Statistical variability in nonlinear spaces: application to shape analysis and dt-mri

Statistical descriptions of anatomical geometry play an important role in many medical image analysis applications. For instance, geometry statistics are useful in understanding the structural changes in anatomy that are caused by growth and disease. Classical statistical techniques can be applied to study geometric data that are elements of a linear space. However, the geometric entities relevant to medical image analysis are often elements of a nonlinear manifold, in which case linear multivariate statistics are not applicable. This dissertation presents a new technique called principal geodesic analysis for describing the variability of data in nonlinear spaces. Principal geodesic analysis is a generalization of a classical technique in linear statistics called principal component analysis, which is a method for computing an efficient parameterization of the variability of linear data. A key feature of principal geodesic analysis is that it is based solely on intrinsic properties, such as the notion of distance, of the underlying data space. The principal geodesic analysis framework is applied to two driving problems in this dissertation: (1) statistical shape analysis using medial representations of geometry, which is applied within an image segmentation framework via posterior optimization of deformable medial models, and (2) statistical analysis of diffusion tensor data intended as a tool for studying white matter fiber connection structures within the brain imaged by magnetic resonance diffusion tensor imaging. It is shown that both medial representations and diffusion tensor data are best parameterized as Riemannian symmetric spaces, which are a class of nonlinear manifolds that are particularly well-suited for principal geodesic analysis. While the applications presented in this dissertation are in the field of medical image analysis, the methods and theory should be widely applicable to many scientific fields, including robotics, computer vision, and molecular biology.
Defining the Ligand-dependent Interactome of the Sigma 1 Receptor

Sigma 1 Receptor (S1R) is a therapeutic target for a wide spectrum of pathological conditions ranging from neurodegenerative diseases to cancer and COVID-19. S1R is ubiquitously expressed throughout the visceral organs, nervous, immune and cardiovascular systems. It is proposed to function as a ligand-dependent molecular chaperone that modulates multiple intracellular signaling pathways. The purpose of this study was to define the S1R interactome under native conditions and upon binding to well-characterized ligands. This was accomplished by fusing the biotin ligase, Apex2, to the C terminus of S1R. Cells stably expressing S1R-Apex or a GFP-Apex control were used to map specific protein interactions. Biotinylated proteins were labeled under native conditions and in a ligand dependent manner, then purified and identified using quantitative mass spectrometry. Under native conditions, S1R biotinylates over 200 novel proteins, many of which localize within the endomembrane system (ER, Golgi, secretory vesicles) and function within the secretory pathway. Under conditions of cellular exposure to either S1R agonist or antagonist, results show enrichment of proteins integral to secretion, extracellular matrix formation, and cholesterol biosynthesis. Notably, Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) displays increased binding to S1R under conditions of treatment with Haloperidol, a well-known S1R antagonist; whereas Low density lipoprotein receptor (LDLR) binds more efficiently to S1R upon treatment with (+)-Pentazocine ((+)-PTZ), a classical S1R agonist. Our results are consistent with the postulated role of S1R as an intracellular chaperone and further suggest important and novel functionalities related to cholesterol metabolism and biosynthesis.
Bone Surface Mapping: a new method for recording detailed human bone surface variation

This paper presents a new method for mapping surface features on bone (e.g. presence and distribution of ochre, surface cuts and scratches, pathologies, etc.). It is an accessible and quantifiable alternative to photogrammetry or three-dimensional scanning. It breaks each bone down into a number of two-dimensional geometric faces that can be utilised in statistical analyses. The number of faces differs depending on the skeletal development of the individual, with children having fewer faces. The recording method allows faces to be grouped by anatomical plane, bone type, side, and region of the body. These selective groupings facilitate flexible categories for hypothesis testing. The technique was developed to enable a detailed recording of ochre staining on human skeletal remains from Khok Phanom Di, Thailand, used in conjunction with a novel recording method to quantify pigment use across the body, and some exemplary results are presented here. While the technique was developed for recording bone surface staining it could also be used to map other variations on bone surfaces, such as in palaeopathological, forensic or taphonomic contexts.
The HERV-K(HML-2) Transcriptome in Non-Diseased Tissue

Human endogenous retrovirus (HERV) transcripts are known to be highly expressed in cancers, yet their activity in non-diseased tissue is largely unknown. Using the GTEx RNA-seq dataset from normal tissue sampled at autopsy, we characterized individual expression of the recent HERV-K(HML-2) provirus group across 13,000 different samples of 54 different tissues from 948 individuals. HML-2 transcripts could be identified in every tissue sampled, and were elevated in the cerebellum, pituitary, testis, and thyroid. 37 different individual proviruses were expressed in one or more tissues, representing all three LTR5 subgroups. 9 proviruses were identified as having LTR-driven transcription, 7 of which belonged to the most recent LTR5HS subgroup. Proviruses of different subgroups displayed a bias in tissue expression which may be associated with differences in transcription factor binding sites in their LTRs. Provirus expression was greater in evolutionarily older proviruses with an earliest shared ancestor of gorilla or older. HML-2 expression was significantly affected by biological sex in one tissue, while age and timing of death (Hardy score) had little effect. Proviruses containing intact gag, pro and env ORFs were expressed in the dataset, with almost every tissue measured potentially expressing at least one intact ORF (gag).
HNRNPA2B1 controls an unfolded protein response-related prognostic gene signature in prostate cancer

HNRNPA2B1 is associated with prostate cancer (PC) disease aggressiveness and underlies pro-tumourigenic cellular stress responses. By analysing >500 PC transcriptomes, we reveal that HNRNPA2B1 over-expression is associated with poor patient prognosis and stress response pathways. These include the “protein processing in the endoplasmic reticulum” (ER) pathway, which incorporates the unfolded protein response (UPR). By RNA-sequencing of HNRNPA2B1-depleted cells PC cells, we identified HNRNPA2B1-mediated down-regulation of UPR genes including the master ER-stress sensor IRE1, which induces ER proteostasis. Consistent with IRE1 down-regulation in HNRNPA2B1-depleted cells, we observed reduced splicing of the IRE1-target and key UPR effector XBP1s. Furthermore, HNRNPA2B1 depletion up-regulates expression of the IRE1-dependent decay (RIDD) target gene BLOC1S1, which is degraded by activated IRE1. We identify a HNRNPA2B1-IRE1-XBP1-controlled four gene prognostic biomarker signature (HIX) which classifies a subgroup of primary PC patients at high risk of disease relapse. Pharmacological targeting of IRE1 attenuated HNRNAPA2-driven PC cell growth. Taken together, our data reveal a putative novel mechanism of UPR activation in PC by HNRNPA2B1, which may promote an IRE1-dependent yet potentially-targetable recurrent disease phenotype.
Flying honeybees adjust their reaction times to enable group cohesion

Flying insects routinely demonstrate coordinated flight in groups. How they achieve this with very limited communication, vision, and neural systems remains an open question. We measured the visual reaction time in flying honeybees while they chased a moving target, and compared in-flight reaction times for solo animals with those flying in groups. Across 425 insects, the solo honeybees show diverse reaction times (an average of 30ms and a standard deviation of 50ms). The reaction times in groups are significantly more uniform (an average of 15ms and a standard deviation of only 7ms), indicating that honeybees in group flight adjust their reaction times to match their neighbors. To investigate the role of this adjustment, we curve fit the reaction time distributions and analyzed them in a mathematical model of swarming, finding that the reaction time increases the stable region of a cohesive swarm. To verify the stabilizing effect was not an artifact of curve fitting, we then inserted the measured delays in a swarm simulation, which breaks apart under the solo reaction times and achieves stable formations for the group reaction times. Together, our findings highlight how flying animals can synchronize their reaction times in group flights to improve group cohesion.
A model of photosynthetic CO 2 assimilation by C 3 leaves accounting for anaplerotic flux 1 into the Calvin-Benson cycle 2

- Plants assimilate carbon primarily via the Calvin-Benson cycle. Analysing isotope abundances 31 in sunflower leaf starch, we recently reported evidence for anaplerotic carbon flux from the 32 plastidial oxidative pentose phosphate pathway into this cycle. Additionally, we reported 33 isotope-derived flux rates ( ν a,p ) at varying atmospheric CO 2 concentration, C a . 34 35 - To test these results by another method, we analysed gas exchange data from the same leaves 36 and experiment by FvCB-type models considering respiration and energy recycling by the 37 plastidial anaplerotic pathway. 38 39 - Consistent with previous results, we found ν a,p proceeds at ≈ 46%, 25%, and 0% relative to 40 net CO 2 assimilation at C a ≈ 180, 280, 450 ppm, respectively. Day respiration proceeds at ≈ 41 58%, 32%, 5%, 8%, and 13% relative to net CO 2 assimilation at C a ≈ 180, 280, 450, 700, and 42 1500 ppm, respectively. Effects of the anaplerotic pathway on metabolism are comprehensively 43 characterised. 44 45 - The results are discussed in relation to regulatory properties of the plastidial and cytosolic 46 anaplerotic pathway, the proposed variability of mesophyll conductance to CO 2 diffusion, and 47 the contribution of day respiration to the A / C i curve drop at high C a . Overall, our work indicates 48 the plastidial anaplerotic pathway is a central component in carbon and energy metabolism of 49 C 3 plants. 50