Miracle-dz/UniFAR-FTUs huggingface dataset:
The endothelial-specific LINC00607 mediates endothelial angiogenic function

Long non-coding RNAs (lncRNAs) can act as regulatory RNAs which, by altering the expression of target genes, impact on the cellular phenotype and cardiovascular disease development. Endothelial lncRNAs and their vascular functions are largely undefined. Deep RNA-Seq and FANTOM5 CAGE analysis revealed the lncRNA LINC00607 to be highly enriched in human endothelial cells. LINC00607 was induced in response to hypoxia, arteriosclerosis regression in non-human primates and also in response to propranolol used to induce regression of human arteriovenous malformations. siRNA knockdown or CRISPR/Cas9 knockout of LINC00607 attenuated VEGF-A-induced angiogenic sprouting. LINC00607 knockout in endothelial cells also integrated less into newly formed vascular networks in an in vivo assay in SCID mice. Overexpression of LINC00607 in CRISPR knockout cells restored normal endothelial function. RNA- and ATAC-Seq after LINC00607 knockout revealed changes in the transcription of endothelial gene sets linked to the endothelial phenotype and in chromatin accessibility around ERG-binding sites. Mechanistically, LINC00607 interacted with the SWI/SNF chromatin remodeling protein BRG1. CRISPR/Cas9-mediated knockout of BRG1 in HUVEC followed by CUT&RUN revealed that BRG1 is required to secure a stable chromatin state, mainly on ERG-binding sites. In conclusion, LINC00607 is an endothelial-enriched lncRNA that maintains ERG target gene transcription by interacting with the chromatin remodeler BRG1.
Social Interaction and Rate Effects in Models of Musical Synchronization

Important individual differences are observed in people’s abilities to synchronize their body movements with regular auditory rhythms. We investigate whether synchronizing with a regular auditory cue is affected by each person’s spontaneous production rate (SPR) and by hearing a partner’s synchronization in a social context. Musically trained and untrained participants synchronized their tapping with an auditory cue presented at different rates (their own SPR or their partner’s SPR) and in a Solo or Joint (turn-taking) condition. Linear and nonlinear oscillator models were fit to participants’ mean asynchronies (signed timing differences between the cued onsets and taps). In Joint turn-taking, participants’ synchrony was increased when the auditory signal was cued at the participant’s own SPR, compared with their partner’s SPR; in contrast, synchronization did not differ across rates in the Solo condition. Asynchronies in the Joint task became larger as the difference between partners’ spontaneous rates increased; the increased asynchronies were driven by the faster partner who did not slow down to match the rate of their slower partner. Nonlinear delay-coupled models (with time delay, coupling strength, and intrinsic frequency) outperformed linear models (intrinsic frequency only) in accounting for tappers’ synchronization adjustments. The nonlinear model’s coupling value increased for musically trained participants, relative to untrained participants. Overall, these findings suggest that both intrinsic differences in partners’ spontaneous rates and the social turn-taking context contribute to the range of synchrony in the general population. Delay-coupled models are capable of capturing the wide range of individual differences in auditory-motor synchronization.
Back From the Dead: The Atypical Kinase Activity of a Pseudokinase Regulator of Cation Fluxes During Inducible Immunity

While most pseudokinases lack phosphotransfer activity due to altered catalytic residues within their kinase domain, a subset of pseudokinases maintain kinase activity through atypical mechanisms. The Arabidopsis ILK1 is a pseudokinase from the Raf-like MAP3K family and is the only known plant pseudokinase with confirmed kinase activity. ILK1 activity promotes microbial pattern-induced root growth inhibition through its stabilization of the HAK5 potassium transporter with the calmodulin-like protein CML9. ILK1 also has a kinase-independent function in salt stress suggesting that it interacts with additional proteins. We determined that members of the ILK subfamily are the sole pseudokinases within the Raf-like MAP3K family and identified 179 novel putative ILK1 protein interactors. We also identified 70 novel peptide targets for ILK1, the majority of which were phosphorylated in the presence of Mn2+ instead of Mg2+ in line with modifications in ILK1’s DFG cofactor binding domain. Overall, the ILK1-targeted or interacting proteins included diverse protein types including transporters (HAK5, STP1), protein kinases (MEKK1, MEKK3), and a cytokinin receptor (AHK2). The expression of 31 genes encoding putative ILK1-interacting or phosphorylated proteins, including AHK2, were altered in the root and shoot in response to molecular patterns suggesting a role for these genes in immunity. We describe a potential role for ILK1 interactors in the context of cation-dependent immune signaling responses, highlighting the importance of K+ in MAMP responses. This work further supports the notion that ILK1 is an atypical kinase with an unusual cofactor dependence that may interact with multiple proteins in the cell.
IL‐21 has a critical role in establishing germinal centers by amplifying early B cell proliferation

The proliferation and differentiation of antigen-specific B cells, including the generation of germinal centers (GC), are prerequisites for long-lasting, high-affinity antibody-mediated immune protection. Affinity for antigen determines B cell recruitment, proliferation, differentiation and competitiveness in the response, largely through determining access to T cell help. However, how T cell derived signals contribute to these outcomes is incompletely understood. Here we report how the signature cytokine of follicular helper T cells, IL-21, acts as a key regulator of the initial B cell response. By activating AKT and S6, IL-21 accelerates cell cycle progression and the rate of cycle entry of B cells, increasing their contribution to the ensuing GC. This effect occurs over a wide range of initial B cell receptor affinities and the resultant increased proliferation can explain the IL-21-mediated promotion of plasma cell differentiation. Collectively, our data establish that IL-21 acts from the outset of a T cell dependent immune response to increase cell cycle progression and fuel cyclic re-entry of B cells thereby regulating the initial GC size and early plasma cell output. Summary The cytokine IL-21 is a regulator of B cell responses, increasing antibody quantity and quality. Here, we report that during germinal center initiation, IL-21 acts to increase the response magnitude by accelerating cell cycle speed and rate of entry.
Computer-aided diagnosis of reflectance confocal images to differentiate between lentigo maligna (LM) and atypical intraepidermal melanocytic proliferation (AIMP)

Lentigo maligna (LM), a form of melanoma in situ that predominantly affects sun-exposed areas such as the face, has an ill-defined clinical border and has a high rate of recurrence. Atypical Intraepidermal Melanocytic Proliferation (AIMP) is a term used to describe the melanocytic proliferation of an uncertain malignant potential. Clinically and histologically, AIMP can be difficult to distinguish from LM, and indeed AIMP may in some cases progress to LM. Reflectance Confocal Microscopy (RCM) is often used to investigate these lesions non-invasively, however, RCM is often not readily available nor is the associated expertise for RCM image interpretation. Here, we demonstrate machine learning architectures that can correctly classify lesions between LM and AIMP on stacks of RCM images. Overall, our methods showcase the potential for computer-aided diagnosis in dermatology, which in conjunction with the remote acquisition, can expand the range of diagnostic tools in the community.
Estimating clade-specific diversification rates and palaeodiversity dynamics from reconstructed phylogenies

Understanding palaeodiversity dynamics through time and space is a central goal of macroevolution. Estimating palaeodiversity dynamics has been historically addressed with fossil data because it directly reflects the past variations of biodiversity. Unfortunately, some groups or regions lack a good fossil record, and dated phylogenies can be useful to estimate diversification dynamics. Recent methodological developments have unlocked the possibility to investigate palaeodiversity dynamics by using phylogenetic birth-death models with non-homogeneous rates through time and across clades. One of them seems particularly promising to detect clades whose diversity has declined through time. However, empirical applications of the method have been hampered by the lack of a robust, accessible implementation of the whole procedure, therefore requiring users to conduct all the steps of the analysis by hand in a time-consuming and error-prone way. Here we propose an automation of Morlon et al. (2011) clade-shift model with additional features accounting for recent developments and we implement it in the R package RPANDA. We also test the approach with simulations focusing on its ability to detect shifts of diversification and to infer palaeodiversity dynamics. Finally, we illustrate the automation by investigating the palaeodiversity dynamics of Cetacea, Vangidae, Parnassiinae, and Cycadales. Simulations showed that we accurately detected shifts of diversification although false shift detections were higher for time-dependent diversification models with extinction. The median global error of palaeodiversity dynamics estimated with the automated model is low showing that the method can capture diversity declines. We detected shifts of diversification for three of the four empirical examples considered (Cetacea, Parnassiinae and Cycadales). Our analyses unveil a waxing-and-waning pattern due to a phase of negative net diversification rate embedded in the trees after isolating recent radiations. Our work makes possible to easily apply non-homogeneous models of diversification in which rates can vary through time and across clades to reconstruct palaeodiversity dynamics. By doing so, we detected palaeodiversity declines among three of the four groups tested, highlighting that such periods of negative net diversification might be common. We discuss the extent to which this approach might provide reliable estimates of extinction rates and we provide guidelines for users.
Microbiome assembly and maintenance across the lifespan of bumble bee workers

How a host’s microbiome changes over its lifespan can influence development and aging. As these temporal patterns have only been described in detail for humans and a handful of other hosts, an important next step is to compare microbiome dynamics across a broader array of host-microbe symbioses, and to investigate how and why they vary. Here we characterize the temporal dynamics and stability of the bumblebee worker gut microbiome. Bumblebees are a useful symbiosis model given their relatively well-understood life history and simple, host-specific gut bacterial communities. Furthermore, microbial dynamics may influence bumblebee health and pollination services. We combined high-temporal-resolution sampling with 16S rRNA gene sequencing, quantitative PCR, and shotgun metagenomics to characterize gut microbiomes over the adult lifespan of Bombus impatiens workers. To understand how hosts may control (or lose control of) the gut microbiome as they age, we also sequenced hindgut transcriptomes. We found that, at the community level, microbiome assembly is highly predictable and similar to patterns of primary succession observed in the human gut. At the same time, partitioning of strain-level bacterial variants among colonies suggests stochastic colonization events similar to those observed in flies and nematodes. We also find strong differences in temporal dynamics among symbiont species, suggesting ecological differences among microbiome members in colonization and persistence. Finally, we show that both the gut microbiome and host transcriptome—including expression of key immunity genes—stabilize, as opposed to senesce, with age. We suggest that in highly social groups such as bumblebees, maintenance of both microbiomes and immunity contribute to the inclusive fitness of workers, and thus remain under selection even in old age. Our findings provide a foundation for exploring the mechanisms and functional outcomes of bee microbiome succession, and for comparative analyses with other host-microbe symbioses.
Identification, Characterization and Mode of Action of Corynaridin, a Novel Linaridin from Corynebacterium lactis

Genome analysis of Corynebacterium lactis revealed a bacteriocin gene cluster encoding a putative bacteriocin of the linaridin family of ribosomally synthesized and posttranslationally modified peptides (RIPPs). The locus harbors typical linaridin modification enzymes but lacks genes for a decarboxylase and methyltransferase, which is unusual for type B linaridins. Supernatants of Corynebacterium lactis RW3-42 showed antimicrobial activity against Corynebacterium glutamicum. Deletion of the precursor gene crdA clearly linked the antimicrobial activity of the producer strain to the identified gene cluster. Following purification, we observed potent activity of the peptide against Actinobacteria, mainly other members of the genus Corynebacterium including the pathogenic species Corynebacterium striatum and Corynebacterium amycolatum. Also, low activity against some Firmicutes was observed, but no activity against Gram-negative species. The peptide is resilient towards heat but sensitive to proteolytic degradation by trypsin and proteinase K. Notably, time-kill kinetics and experiments using live biosensors to monitor membrane integrity suggest bactericidal activity that does not involve formation of pores in the cytoplasmic membrane. As Corynebacterium species are ubiquitous in nature and include important commensal and pathogens of mammalian organisms, secretion of bacteriocins by species of this genus could be a hitherto neglected trait with high relevance for intra- and interspecies competition and infection. Importance Bacteriocins are antimicrobial peptides produced by bacteria to fend off competitors in ecological niches and are considered to be important factors influencing the composition of microbial communities. However, bacteriocin production by bacteria of the genus Corynebacterium has been a hitherto neglected trait, although its species are ubiquitous in nature and make up large parts of the microbiome of humans and animals. In this study, we describe and characterize a novel linaridin-family bacteriocin from Corynebacterium lactis and show its narrow spectrum activity, mainly against other actinobacteria. Moreover, we were able to extend the limited knowledge on linaridin bioactivity in general and for the first time describe the mode of action of such a bacteriocin. Interestingly, the peptide, which was named corynaridin, appears bactericidal, but without formation of pores in the bacterial membrane.
Response of the plant core microbiome to Fusarium oxysporum infection and identification of the pathobiome

Plant core microbiomes consist of persistent key members that provide critical host functions, but their assemblages can be interrupted by biotic and abiotic stresses. The pathobiome is comprised of dynamic microbial interactions in response to disease status of the host. Hence, identifying variation in the core microbiome and pathobiome can significantly advance our understanding of microbial-microbial interactions and consequences for disease progression and host functions. In this study, we combined glasshouse and field studies to analyse the soil and plant rhizosphere microbiome of cotton plants (Gossypium hirsutum) in the presence of a cotton-specific fungal pathogen, Fusarium oxysporum f. sp. vasinfectum (FOV). We found that FOV directly and consistently altered the rhizosphere microbiome, but the biocontrol agents enabled microbial assemblages to resist pathogenic stress. Using co-occurrence network analysis of the core microbiome, we identified the pathobiome comprised of the pathogen and key associate phylotypes in the cotton microbiome. Isolation and application of some negatively correlated pathobiome members provided protection against plant infection. Importantly, our field survey from multiple cotton fields validated the pattern and responses of core microbiomes under FOV infection. This study advances key understanding of core microbiome responses and existence of plant pathobiomes, which provides a novel framework to better manage plant diseases in agriculture and natural settings.
Computational model of fractal interface formation in bacterial biofilms

Bacterial colonies benefit from cellular heterogeneity, with cells differentiating into diverse states of physiology and gene expression. As colonies grow, such cells in distinct states arrange into spatial patterns. To uncover the functional role of these emergent patterns, we must understand how they arise from cellular growth, phenotypic inheritance, and mechanical interactions among cells. Here we present a simple, agent-based model to predict patterns formed by motile and extracellular matrix-producing cells in developing populations of Bacillus subtilis bacteria. By incorporating phenotypic inheritance, differential mechanical interactions of the two cell types, and the escape of peripheral motile cells, our model predicts the emergence of a pattern: matrix cells surround a fractal-like population of interior motile cells. We find that, while some properties of the emergent motile-matrix interface depend on the initial spatial arrangement of cells, the distribution of motile cells at large radii are a product solely of the model’s growth mechanism. Using a box-counting analysis, we find that the emergent motile-matrix interface exhibits a fractal dimension that increases as biofilms grow but eventually reaches a maximum as the thickness of the peripheral layer of matrix exceeds the capacity of the inner cells to push matrix cells out of the way. We find that the presence of the fractal interface correlates with a larger colony growth rate and increases the local proximity of motile and matrix cells, which could promote resource sharing. Our results show that simple computational models can account for morphological features of active systems like bacterial colonies, where colony-level phenotypes emerge from single cell-level properties and cells modifying their own environment. Author summary Like cells in our bodies, bacterial cells can differentiate into different cell types, which perform different roles in colonies. During the growth of Bacillus subtilis colonies, motile cells, which can swim, and matrix cells, which produce sticky polymers to adhere cells together, form reproducible spatial patterns. Multiple factors could drive the formation of these patterns, including inheritance of the motility and matrix states as cells divide, and different mechanical interactions between different cell types as they push each other around during growth. We created an agent-based computational model, in which we represent bacterial cells as occupying squares within a grid. We find that through inheritance of motile and matrix state and greater resistance to physical pushing by matrix cells, our model produces patterns similar to those observed in experiments—an exterior population of matrix cells surrounding an interior group of motile cells with fractal arms that branch into the outer matrix layer. Our results show that simple models can account for complex phenomena like the growth of heterogeneous bacterial colonies.
Detecting more peptides from bottom-up mass spectrometry data via peptide-level target-decoy competition

The analysis of shotgun proteomics data often involves generating lists of inferred peptide-spectrum matches (PSMs) and/or of peptides. The canonical approach for generating these discovery lists is by controlling the false discovery rate (FDR), most commonly through target-decoy competition (TDC). At the PSM level, TDC is implemented by competing each spectrum’s best-scoring target (real) peptide match with its best match against a decoy database. This PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here we first highlight and empirically augment a little-known previous work by He et al., which showed that TDC-based PSM-level FDR estimates can be liberally biased. We thus propose that researchers instead focus on peptide-level analysis. We then investigate three ways to carry out peptide-level TDC and show that the most common method (“PSM-only”) offers the lowest statistical power in practice. An alternative approach that carries out competition at both the PSM and the peptide level (“PSM-and-peptide”) is the most powerful method, yielding an average increase of 17% more discovered peptides at a 1% FDR threshold relative to the PSM-only method.
Distinct gaits of self-propelled quadriflagellate microswimmers

Legged animals often coordinate multiple appendages for both underwater and terrestrial loco-motion. Quadrupeds in particular, change their limb movements dynamically to achieve a number of gaits, such as the gallop, trot, and pronk. Surprisingly, micron-sized unicellular algae are also capable of coordinating four flagella to produce microscale versions of these gaits for swimming. Here we present a fully-3D model of a quadriflagellate microswimmer comprising five beads and systematically investigate the effect of gait on swimming dynamics, propulsion speed, efficiency, and induced flow patterns. We find that by changing gait alone, distinct motility patterns emerge from the same basic microswimmer design. Our findings suggest that different species of morphologically-similar microorganisms (e.g. with identical number and placement of appendages) evolved distinct flagellar coordination patterns as a consequence of different ecological drivers. By comparing the flagella-induced flows in terms of volumetric clearance rate, we further explore the implications of distinct gaits for single-cell dispersal, feeding, and predator-avoidance.