title: Cell free extrachromosomal circular DNA is common in human urine

abstract:
Cell free extrachromosomal circular DNA (eccDNA) is evolving as a potential biomarker in liquid biopsies for disease diagnosis. In this study, an optimized next generation sequencing-based Circle-Seq method was developed to investigate urinary cell free eccDNA (ucf-eccDNA) from 28 adult healthy volunteers (mean age = 28, 19 males/ 9 females). The genomic distributions and sequence compositions of ucf-eccDNAs were comprehensively characterized. Approximately 1.2 million unique ucf-eccDNAs are identified, covering 14.9% of the human genome. Comprehensive characterization of ucf-eccDNAs show that ucf-eccDNAs contain higher GC content than flanking genomic regions. Most eccDNAs are less than 1000 bp and present four pronounced peaks at 203, 361, 550 and 728 bp, indicating the association between eccDNAs and the numbers of intact nucleosomes. Analysis of genomic distribution of ucf-eccDNAs show that eccDNAs are found in all chromosomes but enriched in chromosomes i.e. chr.17, 19 and 20 with high density of protein-codding genes, CpG islands, SINE and simple repeat elements. Lastly, analysis of sequence motif signatures at eccDNA junction sites reveal that direct repeats (DRs) are commonly found, indicating a potential role of DRs in eccDNA biogenesis. This work underscores the deep sequencing analysis of ucf-eccDNAs and provides a valuable reference resource for exploring potential applications of ucf-eccDNA as diagnostic biomarkers of urogenital disorders in the future.

Significance StatementExtrachromosomal circular DNA (eccDNA) is an important genetic element and a biomarker for disease diagnosis and treatment. In this study, we conduct a comprehensive characterization of urinary cell free eccDNA (ucf-eccDNA) in 28 heathy subjects. Over one million ucf-eccDNAs are identified. Ucf-eccDNAs are characterized as high GC content. The size of most ucf-eccDNAs is less than 1000 bp and enriched in four peaks resembling the size of single, double, triple, and quadruple nucleosomes. The genomic distribution of ucf-eccDNAs is enriched in generic regions, protein-coding genes, Alu, CpG islands, SINE and simple repeats. Sequence motif analysis of ucf-eccDNA junctions identified simple direct repeats (DRs) commonly presented in most eccDNAs, suggesting potential roles of DRs in eccDNA biogenesis.

category: genomics


title: A new substrate triggers susceptibility by uncoupling a bacterial multidrug resistance efflux pump

abstract: Small multidrug resistance (SMR) transporters perform coupled antiport of protons and toxic substrates, contributing to antibiotic resistance through efflux of these compounds from the bacterial cytoplasm. Extensive biophysical studies of the molecular transport mechanism of the E. coli SMR transporter EmrE indicate that it should also be capable of performing proton/drug symport or uniport, either of which will lead to drug susceptibility rather than drug resistance in vivo. Here we show that EmrE does indeed confer susceptibility to some small molecule substrates in the native E. coli in addition to conferring resistance to known polyaromatic cation substrates. In vitro experiments show that substrate binding at a secondary site triggers uncoupled proton uniport that leads to susceptibility. These results suggest that the SMR transporters provide one avenue for bacterial-selective dissipation of the proton-motive force. This has potential for antibiotic development and disruption of antibiotic resistance due to drug efflux more broadly.

category: biochemistry


title: Sterilization of drug-resistant influenza virus through genetic interference: use of unnatural amino acid-engineered virions

abstract: The frequent emergence of drug resistance during the treatment of influenza A virus (IAV) infections highlights a need for effective antiviral countermeasures. Here, we present an antiviral method that utilizes unnatural amino acid-engineered drug-resistant (UAA-DR) virus. The engineered virus is generated through genetic code expansion to combat emerging drug-resistant viruses. The UAA-DR virus has unnatural amino acids incorporated into its drug-resistant protein and its polymerase complex for replication control. The engineered virus can undergo genomic segment reassortment with normal virus and produce sterilized progenies due to artificial amber codons in the viral genome. We validate in vitro that UAA-DR can provide a broad-spectrum antiviral strategy for several H1N1 strains, different DR-IAV strains, multidrug-resistant (MDR) strains, and even antigenically distant influenza strains (e.g., H3N2). Moreover, a minimum dose of neuraminidase (NA) inhibitors for influenza virus can further enhance the sterilizing effect when combating inhibitor-resistant strains, partly due to the promoted superinfection of unnatural amino acid-modified virus in cellular and animal models. We also exploited the engineered virus to achieve adjustable efficacy after external UAA administration, for mitigating DR virus infection on transgenic mice harboring the [Formula] pair, and to have substantial elements of the genetic code expansion technology, which further demonstrated the safety and feasibility of the strategy. We anticipate that the use of the UAA-engineered DR virion, which is a novel antiviral agent, could be extended to combat emerging drug-resistant influenza virus and other segmented RNA viruses.

category: bioengineering


title: Axial Stress Provides a Lower Bound on Shear Wave Velocity in Active and Passive Muscle

abstract: Ultrasound shear wave elastography can be used to characterize mechanical properties of unstressed tissue by measuring shear wave velocity (SWV), which increases with increasing tissue stiffness. Measurements of SWV have often been assumed to be directly related to the stiffness of muscle. Some have also used measures of SWV to estimate stress, since muscle stiffness and stress covary during active contractions. However, few have considered the direct influence of muscle stress on SWV, independent of the stress-dependent changes in muscle stiffness, even though it is well known that stress alters shear wave propagation. The objective of this study was to determine how well the theoretical dependency of SWV on stress can account for measured changes of SWV in passive and active muscle. Data were collected from six isoflurane-anesthetized cats; three soleus muscles and three medial gastrocnemius muscles. Muscle stress and stiffness were measured directly along with SWV. Measurements were made across a range of passively and actively generated stresses, obtained by varying muscle length and activation, which was controlled by stimulating the sciatic nerve. Our results show that SWV depends primarily on the stress in a passively stretched muscle. In contrast, the SWV in active muscle is higher than would be predicted by considering only stress, presumably due to activation-dependent changes in muscle stiffness. Our results demonstrate that while SWV is sensitive to changes in muscle stress and activation, there is not a unique relationship between SWV and either of these quantities when considered in isolation.


title: Robust Single-cell Matching and Multi-modalAnalysis Using Shared and Distinct FeaturesReveals Orchestrated Immune Responses

abstract: The ability to align individual cellular information from multiple experimental sources, techniques and systems is fundamental for a true systems-level understanding of biological processes. While single-cell transcriptomic studies have transformed our appreciation for the complexities and contributions of diverse cell types to disease, they can be limited in their ability to assess protein-level phenotypic information and beyond. Therefore, matching and integrating single-cell datasets which utilize robust protein measurements across multiple modalities is critical for a deeper understanding of cell states, and signaling pathways particularly within their native tissue context. Current available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely upon a large number of shared features across datasets for mutual Nearest Neighbor (mNN) matching. This approach is unsuitable when applied to single-cell proteomic datasets, due to the limited number of parameters simultaneously accessed, and lack of shared markers across these experiments. Here, we introduce a novel cell matching algorithm, Matching with pARtIal Overlap (MARIO), that takes into account both shared and distinct features, while consisting of vital filtering steps to avoid sub-optimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multi-modal methods, including spatial techniques, and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via CODEX imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid via CITE-seq. This cross-platform integrative analysis enabled the identification of unique orchestrated immune responses within the lung of complement-expressing macrophages and their impact on the local tissue microenvironment. MARIO thus provides an analytical framework for unified analysis of single-cell data for a comprehensive understanding of the underlying biological system.

category: bioinformatics


title: Biofilm Growth Under Elastic Confinement

abstract: Bacteria often form surface-bound communities, embedded in a self-produced extracellular matrix, called biofilms. Quantitative studies of their growth have typically focused on unconfined expansion above solid or semi-solid surfaces, leading to exponential radial growth. This geometry does not accurately reflect the natural or biomedical contexts in which biofilms grow in confined spaces. Here we consider one of the simplest confined geometries: a biofilm growing laterally in the space between a solid surface and an overlying elastic sheet. A poroelastic framework is utilised to derive the radial growth rate of the biofilm; it reveals an additional self-similar expansion regime, governed by the stiffness of the matrix, leading to a finite maximum radius, consistent with our experimental observations of growing Bacillus subtilis biofilms confined by PDMS.

category: biophysics


title: Reduced Dimension, Biophysical Neuron Models Constructed From Observed Data

abstract:
Using methods from nonlinear dynamics and interpolation techniques from applied mathematics, we show how to use data alone to construct discrete time dynamical rules that forecast observed neuron properties. These data may come from from simulations of a Hodgkin-Huxley (HH) neuron model or from laboratory current clamp experiments. In each case the reduced dimension data driven forecasting (DDF) models are shown to predict accurately for times after the training period.

When the available observations for neuron preparations are, for example, membrane voltage V(t) only, we use the technique of time delay embedding from nonlinear dynamics to generate an appropriate space in which the full dynamics can be realized.

The DDF constructions are reduced dimension models relative to HH models as they are built on and forecast only observables such as V(t). They do not require detailed specification of ion channels, their gating variables, and the many parameters that accompany an HH model for laboratory measurements, yet all of this important information is encoded in the DDF model.

As the DDF models use only voltage data and forecast only voltage data, they can be used in building networks with biophysical connections. Both gap junction connections and ligand gated synaptic connections among neurons involve presynaptic voltages and induce postsynaptic voltage response. Biophysically based DDF neuron models can replace other reduced dimension neuron models, say of the integrate-and-fire type, in developing and analyzing large networks of neurons.

When one does have detailed HH model neurons for network components, a reduced dimension DDF realization of the HH voltage dynamics may be used in network computations to achieve computational efficiency and the exploration of larger biological networks.


title: Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors: Dependencies and Novel Pitfalls

abstract: Personalized Oncology is a rapidly evolving area and offers cancer patients therapy options more specific than ever. Yet, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation Projection (UMAP)) on three datasets of metastases (n=682 samples) with three different data transformations (unprocessed, log10 as well as log10+1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n=616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between site of resection and cluster formation outcome could be demonstrated, neither for datasets consisting of solely metastasis nor mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results indicate only minor transcriptional differences for metastases and corresponding primary tumors.

category: cancer biology


title: Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors - Dependencies and Novel Pitfalls


title: Quantifying the Invasive Secondary Metabolome

abstract:
Invasive plants drive ecosystem degradation through developing aggressive phenotypes that can outcompete native flora. Several hypotheses explain this, like the Evolution of Increased Competitive Ability hypothesis and the Novel Weapons Hypothesis, but none have been proven conclusively. Changes in plant metabolites are critical to these hypotheses, but complete invasive secondary metabolomes have not been quantified. Here, statistical and unsupervised machine-learning approaches were used to analyse chemotype-to-phenotype relationships in invasive and non-invasive populations in species Ageratum conyzoides, Lantana camara, Melaleuca quinquenervia and Psidium cattleainum and on a family level analysing Asteraceae, Myrtaceae and Verbenaceae. Invasive metabolomes evolved according to the EICA and NWH, involving optimisation of aggressive strategies present in native populations and local adaptation.

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category: plant biology


title: Deep-learning microscopy image reconstruction with quality control reveals second-scale rearrangements in RNA polymerase II clusters

abstract: Fluorescence microscopy, a central tool of biological research, is subject to inherent trade-offs in experiment design. For instance, image acquisition speed can only be increased in exchange for a lowered signal quality, or for an increased rate of photo-damage to the specimen. Computational denoising can recover some loss of signal, extending the trade-off margin for high-speed imaging. Recently proposed denoising on the basis of neural networks shows exceptional performance but raises concerns of errors typical of neural networks. Here, we present a work-flow that supports an empirically optimized reduction of exposure times, as well as per-image quality control to exclude images with reconstruction errors. We implement this work-flow on the basis of the denoising tool Noise2Void and assess the molecular state and three-dimensional shape of RNA Polymerase II (Pol II) clusters in live zebrafish embryos. Image acquisition speed could be tripled, achieving 2-second time resolution and 350-nanometer lateral image resolution. The obtained data reveal stereotyped events of approximately 10 seconds duration: initially, the molecular mark for initiated Pol II increases, then the mark for active Pol II increases, and finally Pol II clusters take on a stretched and unfolded shape. An independent analysis based on fixed sample images reproduces this sequence of events, and suggests that they are related to the transient association of genes with Pol II clusters. Our work-flow consists of procedures that can be implemented on commercial fluorescence microscopes without any hardware or software modification, and should therefore be transferable to many other applications.

category: systems biology


title: Neuron particles capture network topology and behavior from single units

abstract: While networks of neurons, glia and vascular systems enable and support brain functions, to date, mathematical tools to decode network dynamics and structure from very scarce and partially observed neuronal spiking behavior remain underdeveloped. Large neuronal networks contribute to the intrinsic neuron transfer function and observed neuronal spike trains encoding complex causal information processing, yet how this emerging causal fractal memory in the spike trains relates to the network topology is not fully understood. Towards this end, we propose a novel statistical physics inspired neuron particle model that captures the causal information flow and processing features of neuronal spiking activity. Relying on synthetic comprehensive simulations and real-world neuronal spiking activity analysis, the proposed fractional order operators governing the neuronal spiking dynamics provide insights into the memory and scale of the spike trains as well as information about the topological properties of the underlying neuronal networks. Lastly, the proposed model exhibits superior predictions of animal behavior during multiple cognitive tasks.

category: neuroscience


title: A Computational Model of Stereoscopic Prey Capture inPraying Mantises

abstract: We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single "disparity sensor": a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the known behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory surround, making them tuned to size. The disparity sensor combines inputs from the two eyes linearly, applies a threshold and then an exponent output nonlinearity. The activity of the sensor represents the model mantiss instantaneous probability of striking. We integrate this over the stimulus duration to obtain the expected number of strikes in response to moving targets with different stereoscopic distance, size and vertical disparity. We optimised the parameters of the model so as to bring its predictions into agreement with our empirical data on mean strike rate as a function of stimulus size and distance. The model proves capable of reproducing the relatively broad tuning to size and narrow tuning to stereoscopic distance seen in mantis striking behaviour. The model also displays realistic responses to vertical disparity. Most surprisingly, although the model has only a single centre-surround receptive field in each eye, it displays qualitatively the same interaction between size and distance as we observed in real mantids: the preferred size increases as prey distance increases beyond the preferred distance. We show that this occurs because of a stereoscopic "false match" between the leading edge of the stimulus in one eye and its trailing edge in the other; further work will be required to find whether such false matches occur in real mantises. This is the first image-computable model of insect stereopsis, and reproduces key features of both neurophysiology and striking behaviour.


title: HippUnfold: Automated hippocampal unfolding, morphometry, and subfield segmentation

abstract: Like neocortical structures, the archicortical hippocampus differs in its folding patterns across individuals. Here, we present an automated and robust BIDS-App, HippUnfold, for defining and indexing individual-specific hippocampal folding in MRI, analogous to popular tools used in neocortical reconstruction. Such tailoring is critical for inter-individual alignment, with topology serving as the basis for homology. This topological framework enables qualitatively new analyses of morphological and laminar structure in the hippocampus or its subfields. It is critical for refining current neuroimaging analyses at a meso- as well as micro-scale. HippUnfold uses state-of-the-art deep learning combined with previously developed topological constraints to generate uniquely folded surfaces to fit a given subjects hippocampal conformation. It is designed to work with commonly employed sub-millimetric MRI acquisitions, with possible extension to microscopic resolution. In this paper we describe the power of HippUnfold in feature extraction, and highlight its unique value compared to several extant hippocampal subfield analysis methods.


title: Topographically localised modulation of tectal cell spatial tuning by natural scenes

abstract: Visual neurons can have their tuning properties contextually modulated by the presence of visual stimuli in the area surrounding their receptive field, especially when that stimuli contains natural features. However, stimuli presented in specific egocentric locations may have greater behavioural relevance, raising the possibility that the extent of contextual modulation may vary with position in visual space. To explore this possibility we utilised the small size and optical transparency of the larval zebrafish to describe the form and spatial arrangement of contextually modulated cells throughout an entire tectal hemisphere. We found that the spatial tuning of tectal neurons to a prey-like stimulus sharpens when the stimulus is presented in the context of a naturalistic visual scene. These neurons are confined to a spatially restricted region of the tectum and have receptive fields centred within a region of visual space in which the presence of prey preferentially triggers hunting behaviour. Our results demonstrate that circuits that support behaviourally relevant modulation of tectal neurons are not uniformly distributed. These findings add to the growing body of evidence that the tectum shows regional adaptations for behaviour.


title: Intraspecific variation in migration timing of green sturgeon in the Sacramento River system

abstract:
BackgroundUnderstanding movement patterns of anadromous fishes is critical to conservation management of declining wild populations and preservation of habitats. Yet, infrequent observations of individual animals fundamentally constrain accurate descriptions of movement dynamics.

MethodsIn this study, we synthesized over a decade (2006-2018) of acoustic telemetry tracking observations of green sturgeon (Acipenser medirostris) in the Sacramento River system to describe major anadromous movement patterns.

ResultsWe observed that green sturgeon exhibited a unimodal in-migration during the spring months but had a bimodal distribution of out-migration timing, split between an  early out-migration (32%) group during May - June, or alternatively, holding in the river until a  late out-migration (68%), November - January. Focusing on these out-migration groups, we found that river discharge, but not water temperature, may cue the timing of migration, and that fish showed a tendency to maintain out-migration timing between subsequent spawning migration events.

ConclusionsWe recommend that life history descriptions of green sturgeon in this region reflect the distinct out-migration periods described here. Furthermore, we encourage the continued use of biotelemetry to describe migration timing and life history variation, not only this population but other green sturgeon populations and other species.

category: ecology


title: The p53 transactivation domain 1-dependent response to acute DNA damage in endothelial cells protects against radiation-induced cardiac injury

abstract: Thoracic radiation therapy can cause endothelial injury in the heart, leading to cardiac dysfunction and heart failure. Although it has been demonstrated that the tumor suppressor p53 functions in endothelial cells to prevent the development of radiation-induced myocardial injury, the key mechanism(s) by which p53 regulates the radiosensitivity of cardiac endothelial cells is not completely understood. Here, we utilized genetically engineered mice that express mutations in p53 transactivation domain 1 (TAD1) (p5325,26) or mutations in p53 TAD1 and TAD2 (p5325,26,53,54) specifically in endothelial cells to study the p53 transcriptional program that protects cardiac endothelial cells from ionizing radiation in vivo. p5325,26,53,54 loses the ability to drive transactivation of p53 target genes after irradiation while p5325,26 can induce transcription of a group of non-canonical p53 target genes, but not the majority of classic radiation-induced p53 targets critical for p53-mediated cell cycle arrest and apoptosis. After 12 Gy whole-heart irradiation, we found that both p5325,26 and p5325,26,53,54 sensitized mice to radiation-induced cardiac injury, in contrast to wild-type p53. Histopathological examination suggested that mutation of TAD1 contributes to myocardial necrosis after whole-heart irradiation, while mutation of both TAD1 and TAD2 abolishes the ability of p53 to prevent radiation-induced heart disease. Taken together, our results show that the transcriptional program downstream of p53 TAD1, which activates the acute DNA damage response after irradiation, is necessary to protect cardiac endothelial cells from radiation injury in vivo.

category: genetics


title: TbasCO: Trait-based Comparative 'Omics Identifies Ecosystem-Level and Niche-Differentiating Adaptations of an Engineered Microbiome

abstract: A grand challenge in microbial ecology is disentangling the traits of individual populations within complex communities. Various cultivation-independent approaches have been used to infer traits based on the presence of marker genes. However, marker genes are not linked to traits with complete fidelity, nor do they capture important attributes, such as the timing of expression or coordination among traits. To address this, we present an approach for assessing the trait landscape of microbial communities by statistically defining a trait attribute as shared transcriptional pattern across multiple organisms. Leveraging the KEGG pathway database as a trait library and the Enhanced Biological Phosphorus Removal (EBPR) model microbial ecosystem, we demonstrate that a majority (65%) of traits present in 10 or more genomes have niche-differentiating expression attributes. For example, while 14 genomes containing the high-affinity phosphorus transporter pstABCS display a canonical attribute (e.g. up-regulation under phosphorus starvation), we identified another attribute shared by 11 genomes where transcription was highest under high phosphorus conditions. Taken together, we provide a novel framework for revealing hidden metabolic versatility when investigating genomic data alone by assigning trait-attributes through genome-resolved time-series metatranscriptomics.


title: Massively Parallel Selection of NanoCluster Beacons

abstract: NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed the polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here we report a high-throughput selection method that takes advantage of repurposed next-generation-sequencing (NGS) chips to screen the activation fluorescence of [~]40,000 activator sequences. We find the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow and red POTs, respectively. Based on these findings, we propose a "zipper bag model" that explains how these hotspots lead to the creation of distinct silver cluster chromophores and contribute to the difference in chromophore chemical yields. Combining high-throughput screening with machine learning algorithms, we establish a pipeline to rationally design bright and multicolor NCBs.


title: KAGE: Fast alignment-free graph-based genotyping of SNPs and short indels

abstract: Genotyping is a core application of high-throughput sequencing. We present KAGE, a genotyper for SNPs and short indels that is inspired by recent developments within graph-based genome representations and alignment-free methods. KAGE uses a pan-genome representation of the population to efficiently and accurately predict genotypes. Two novel ideas improve both the speed and accuracy: a Bayesian model incorporates genotypes from thousands of individuals to improve prediction accuracy, and a computationally efficient method leverages correlation between variants. We show that the accuracy of KAGE is at par with the best existing alignment-free genotypers, while being an order of magnitude faster.


title: Horizontal gene transfer facilitates the spread of extracellular antibiotic resistance genes in soil

abstract:
Antibiotic resistance genes (ARGs) are ubiquitous in the environment and pose a serious risk to human and veterinary health. While many studies focus on the spread of live antibiotic resistant bacteria throughout the environment, it is unclear whether extracellular ARGs from dead cells can transfer to live bacteria to facilitate the evolution of antibiotic resistance in nature. Here, we inoculate antibiotic-free soil with extracellular ARGs (eARGs) from dead Pseudeononas stutzeri cells and track the evolution of antibiotic resistance via natural transformation - a mechanism of horizontal gene transfer involving the genomic integration of eARGs. We find that transformation facilitates the rapid evolution of antibiotic resistance even when eARGs occur at low concentrations (0.25 g g-1 soil). However, when eARGs are abundant, transformation increases substantially. The evolution of antibiotic resistance was high under soil moistures typical in terrestrial systems (5%-30% gravimetric water content) and was only inhibited at very high soil moistures (>30%). While eARGs transformed into live cells at a low frequency, exposure to a low dose of antibiotic allowed a small number of transformants to reach high abundances in laboratory populations, suggesting even rare transformation events pose a risk to human health. Overall, this work demonstrates that dead bacteria and their eARGs are an overlooked path to antibiotic resistance, and that disinfection alone is insufficient to stop the spread of antibiotic resistance. More generally, the spread of eARGs in antibiotic-free soil suggests that transformation allows genetic variants to establish at low frequencies in the absence of antibiotic selection.

ImportanceOver the last decade, antibiotics in the environment have gained increasing attention because they can select for drug-resistant phenotypes that would have otherwise gone extinct. To counter this effect, bacterial populations exposed to antibiotics often undergo disinfection. However, the release of extracellular antibiotic resistance genes (eARGs) into the environment following disinfection can promote the transfer of eARGs through natural transformation. This phenomenon is well-documented in wastewater and drinking water, but yet to be investigated in soil. Our results directly demonstrate that eARGs from dead bacteria are an important, but often overlooked source of antibiotic resistance in soil. We conclude that disinfection alone is insufficient to prevent the spread of ARGs. Special caution should be taken in releasing antibiotics into the environment, even if there are no live antibiotic resistant bacteria in the community, as transformation allows DNA to maintain its biological activity past microbial death.

category: microbiology


title: Environmentally-induced DNA methylation is inherited across generations in an aquatic keystone species (Daphnia magna)

abstract:
Environmental stress can result in epigenetic modifications that are passed down several generations. Such epigenetic inheritance can have significant impact on eco-evolutionary dynamics, but the phenomenon remains controversial in ecological model systems. Here, we used whole-genome bisulfite sequencing on individual water fleas (Daphnia magna) to assess whether environmentally-induced DNA methylation can persist for up to four generations. Genetically identical females were exposed to a control treatment, one of three natural stressors (high temperature, zinc, microcystin), or the methylation-inhibitor 5-azacytidine. After exposure, lines were propagated clonally for four generations under control conditions. We identified between 70 and 225 differentially methylated CpG positions (DMPs) between controls and F1 individuals whose mothers (and therefore they themselves as germ cells) were exposed to one of the three natural stressors. Between 46% and 58% of these environmentally-induced DMPs persisted until generation F4 without attenuation in their magnitude of differential methylation. DMPs were enriched in exons and largely stressor-specific, suggesting a possible role in environment-dependent gene regulation. In contrast, treatment with the compound 5-azacytidine demonstrated that pervasive hypo-methylation upon exposure is reset almost completely after a single generation. These results suggest that environmentally-induced DNA methylation is non-random and stably inherited across generations in Daphnia, making epigenetic inheritance a putative factor in the eco-evolutionary dynamics of fresh-water communities.

Author summaryWater fleas are important keystone species mediating eco-evolutionary dynamics in lakes and ponds. It is currently an open question in how far epigenetic inheritance contributes to the ability of Daphnia populations to adapt to environmental stress. Using a range of naturally occurring stressors and a multi-generational design, we show that environmentally-induced DNA methylation variants are stably inherited for at least four generations in Daphnia magna. The induced variation in DNA methylation are stressor-specific and almost exclusively found in exons, bearing the signatures of functional adaptations. Our findings imply that ecological adaptations of Daphnia to seasonal fluctuations can be underpinned by epigenetic inheritance of DNA methylation without changes in gene frequencies.

category: evolutionary biology


title: A point mutation in the nucleotide exchange factor eIF2B constitutively activates the integrated stress response by allosteric modulation

abstract: In eukaryotic cells, stressors reprogram the cellular proteome by activating the integrated stress response (ISR). In its canonical form, stress-sensing kinases phosphorylate the eukaryotic translation initiation factor eIF2 (eIF2-P), which ultimately leads to reduced levels of ternary complex required for initiation of mRNA translation. Translational control is primarily exerted through a conformational switch in eIF2s nucleotide exchange factor, eIF2B, which shifts from its active A-State conformation to its inhibited I-State conformation upon eIF2-P binding, resulting in reduced nucleotide exchange on eIF2. Here, we show functionally and structurally how a single histidine to aspartate point mutation in eIF2Bs {beta} subunit (H160D) mimics the effects of eIF2-P binding by promoting an I-State like conformation, resulting in eIF2-P independent activation of the ISR. These findings corroborate our previously proposed (Schoof et al. 2021) A/I-State model of allosteric ISR regulation.

category: molecular biology


title: Obesity affects mitochondrial metabolism and proliferative potential of endometrial progenitor cells

abstract: The study aimed to investigate the influence of obesity on cellular features of equine endometrial progenitor cells (Eca EPCs), including viability, proliferation capacity, mitochondrial metabolism, and oxidative homeostasis. Eca EPCs derived from non-obese (Non-OB) and obese (OB) mares were characterized by cellular phenotype and multipotency. Obesity-induced changes in the activity of Eca EPCs include the decline of their proliferative activity, clonogenic potential, mitochondrial metabolism and enhanced oxidative stress. Eca EPCs isolated from obese mares were characterized by an increased occurrence of early apoptosis, loss of mitochondrial dynamics, and senescence-associated phenotype. Attenuated metabolism of Eca EPCs OB was related to increased expression of pro-apoptotic markers (CASP9, BAX, P53, P21), enhanced expression of OPN, PI3K and AKT, simultaneously with decreased signaling stabilizing cellular homeostasis (including mitofusin, SIRT1, FOXP3). Obesity alters functional features and the self-renewal potential of endometrial progenitor cells. The impaired cytophysiology of progenitor cells from obese endometrium predict lower regenerative capacity if used as autologous transplants.

category: cell biology


title: Obesity affects mitochondrial metabolism and proliferative potential of equine endometrial progenitor cells.


title: Conditional Freezing, Flight and Darting?

abstract: Fear conditioning is one of the most frequently used laboratory procedures for modeling learning and memory generally, and anxiety disorders in particular. The conditional response (CR) used in the majority of fear conditioning studies in rodents is freezing. Recently, it has been reported that under certain conditions, running, jumping or darting replaces freezing as the dominant CR. These findings raise both a critical methodological problem and an important theoretical issue. If only freezing is measured but rodents express their learning with a different response, then significant instances of learning, memory, or fear may be missed. In terms of theory, whatever conditions lead to these different behaviors may be a key to how animals transition between different defensive responses and different emotional states. We replicated these past results but along with several novel control conditions. Contrary to the prior conclusions, running and darting were entirely a result of nonassociative processes and were actually suppressed by associative learning. Darting and flight were taken to be analogous to nonassociative startle or alpha responses that are potentiated by fear. On the other hand, freezing was the purest reflection of associative learning. We also uncovered a rule that describes when these movements replace freezing: When afraid, freeze until there is a sudden novel change in stimulation, then burst into vigorous flight attempts. This rule may also govern the change from fear to panic.

category: animal behavior and cognition


title: Structure of the RZZ complex and molecular basis of Spindly-driven corona assembly at human kinetochores

abstract: In metazoans, a {asymp}1 megadalton (MDa) super-complex comprising the Dynein-Dynactin adaptor Spindly and the ROD-Zwilch-ZW10 (RZZ) complex is the building block of a fibrous biopolymer, the kinetochore fibrous corona. The corona assembles on mitotic kinetochores to promote microtubule capture and spindle assembly checkpoint (SAC) signaling. We report here a high-resolution cryo-EM structure that captures the essential features of the RZZ complex, including a farnesyl binding site required for Spindly binding. Using a highly predictive in vitro assay, we demonstrate that the SAC kinase MPS1 is necessary and sufficient for corona assembly at supercritical concentrations of the RZZ-Spindly (RZZS) complex, and describe the molecular mechanism of phosphorylation-dependent filament nucleation. We identify several structural requirements for RZZS polymerization in rings and sheets. Finally, we identify determinants of kinetochore localization and corona assembly of Spindly. Our results describe a framework for the long-sought-for molecular basis of corona assembly on metazoan kinetochores.


abstract:
Learning generalizable, transferable, and robust representations for molecule data has always been a challenge. The recent success of contrastive learning (CL) for self-supervised graph representation learning provides a novel perspective to learn molecule representations. The most prevailing graph CL framework is to maximize the agreement of representations in different augmented graph views. However, existing graph CL frameworks usually adopt stochastic augmentations or schemes according to pre-defined rules on the input graph to obtain different graph views in various scales (e.g. node, edge, and subgraph), which may destroy topological semantemes and domain prior in molecule data, leading to suboptimal performance. Therefore, designing parameterized, learnable, and explainable augmentation is quite necessary for molecular graph contrastive learning. A well-designed parameterized augmentation scheme can preserve chemically meaningful structural information and intrinsically essential attributes for molecule graphs, which helps to learn representations that are insensitive to perturbation on unimportant atoms and bonds. In this paper, we propose a novel Molecular Graph Contrastive Learning with Parameterized Explainable Augmentations, MolCLE for brevity, that self-adaptively incorporates chemically significative information from both topological and semantic aspects of molecular graphs. Specifically, we apply deep neural networks to parameterize the augmentation process for both the molecular graph topology and atom attributes, to highlight contributive molecular substructures and recognize underlying chemical semantemes. Comprehensive experiments on a variety of real-world datasets demonstrate that our proposed method consistently outperforms compared baselines, which verifies the effectiveness of the proposed framework. Detailedly, our self-supervised MolCLE model surpasses many supervised counterparts, and meanwhile only uses hundreds of thousands of parameters to achieve comparative results against the state-of-the-art baseline, which has tens of millions of parameters. We also provide detailed case studies to validate the explainability of augmented graph views.

CCS CONCEPTS* Mathematics of computing [->] Graph algorithms; * Applied computing [->] Bioinformatics; * Computing methodologies [->] Neural networks; Unsupervised learning.


title: DARTS: an Algorithm for Domain-Associated RetroTransposon Search in Genome Assemblies

abstract: Retrotransposons comprise a substantial fraction of eukaryotic genomes reaching the highest proportions in plants. Therefore, identification and annotation of retrotransposons is an important task in studying regulation and evolution of plant genomes. A majority of computational tools for mining transposable elements (TEs) are designed for subsequent genome repeat masking, often leaving aside the element lineage classification and its protein domain composition. Additionally, studies focused on diversity and evolution of a particular group of retrotransposons often require substantial customization efforts from researchers to adapt existing software to their needs. Here, we developed a computational pipeline to mine sequences of protein-coding retrotransposons based on the sequences of their conserved protein domains - DARTS. Using the most abundant group of TEs in plants - long terminal repeat (LTR) retrotransposons (LTR-RTs), we show that DARTS has radically higher sensitivity of LTR-RTs identification compared to a widely accepted LTRharvest tool. DARTS can be easily customized for specific user needs. As a result, DARTS returns a set of structurally annotated nucleotide and amino acid sequences which can be readily used in subsequent comparative and phylogenetic analyses. DARTS should facilitate researchers interested in discovery and in-detail analysis of diversity and evolution of retrotransposons, LTR-RTs, and other protein-coding TEs.


title: SlTDP1 Is Required To Specify Tapetum Identity And For The Regulation Of Redox Homeostasis In Tomato Anthers

abstract:
The tapetum is a specialized layer of cells within the anther adjacent to the sporogenic tissue. During its short life, it provides nutrients, molecules and materials to the pollen mother cells and microsporocytes being essential during callose degradation and pollen wall formation. However, the acquisition of tapetal cell identity in tomato plants is a process still poorly understood. We report here the identification and characterization of SlTPD1 (Solanum lycopersicum TPD1), a gene specifically required for pollen development in tomato plants. Gene editing was used to generate loss-of-function Sltpd1 mutants that showed absence of tapetal tissue. In these plants, sporogenous cells developed but failed to complete meiosis resulting in complete male sterility. Transcriptomic analysis conducted in wild-type and mutant anthers at an early stage revealed the down regulation of a set of genes related to redox homeostasis. Indeed, Sltpd1 anthers showed a reduction of reactive oxygen species (ROS) accumulation at early stages and altered activity of ROS scavenging enzymes. The obtained results highlight the importance of ROS homeostasis in the interaction between the tapetum and the sporogenous tissue in tomato plants.

One sentence summaryThe small protein SlTPD1 is required for tapetum formation in tomato, highlighting the role of this tissue in the regulation of redox homeostasis during male gametogenesis.


title: COP1 promotes seed germination by destabilizing RGA-LIKE2 (RGL2) in Arabidopsis

abstract: Under favorable moisture, temperature and light conditions, gibberellin (GA) biosynthesis is induced and triggers seed germination. A major mechanism by which GA promotes seed germination is by promoting the degradation of the DELLA protein RGL2, a major repressor of germination in Arabidopsis seeds. Analysis of seed germination phenotypes of constitutively photomorphogenic 1 (cop1) mutants and complemented COP1-OX/cop1-4 lines in response to GA and paclobutrazol (PAC) suggested a positive role for COP1 in seed germination and a relation with GA signaling. cop1-4 mutant seeds showed PAC hypersensitivity, but transformation with a COP1 overexpression construct rendered them PAC insensitive, with a phenotype similar to that of rgl2 mutant (rgl2-SK54) seeds. Furthermore, cop1-4 rgl2-SK54 double mutants showed a PAC-insensitive germination phenotype like that of rgl2-SK54, identifying COP1 as an upstream negative regulator of RGL2. COP1 interacts directly with RGL2 and in vivo this interaction is strongly enhanced by SPA1. COP1 directly ubiquitinates RGL2 to promote its degradation. Moreover, GA stabilizes COP1 with consequent RGL2 destabilization. By uncovering this COP1-RGL2 regulatory module, we reveal a novel mechanism whereby COP1 positively regulates seed germination and controls the expression of germination-promoting genes.


title: From fruit growth to ripening in plantain: a careful balance between carbohydrate synthesis and breakdown

abstract: We investigated the fruit development in two plantain banana cultivars from two weeks after bunch emergence till twelve weeks through high-throughput proteomics, major metabolite quantification and metabolic flux analyses. We give for the first time an insight at early stages of starch synthesis and breakdown. Starch and sugar synthesis and breakdown are processes that take place simultaneously. During the first eight to ten weeks the balance between synthesis and breakdown is clearly in favour of sugar breakdown and a net starch synthesis occurs. During this period, plantain fruit accumulates up to 48% of starch. The initiation of the ripening process is accompanied with a shift in balance towards net starch breakdown. The key enzymes related to this are phosphoglucan water dikinase (PWD), phosphoglucan phosphatase, -1,6-glucosidase starch debranching enzyme (DBE), alpha glucan phosphorylase (PHS) and 4-alpha glucanotransferase disproportioning enzyme (DPE). The highest correlations with sucrose have been observed for PHS and DPE. There is also a significant correlation between the enzymes involved in ethylene biosynthesis, starch breakdown, pulp softening and ascorbate biosynthesis. The faster ending of maturation and starting of ripening in the Agbagba cultivar are linked to the key enzymes 1-aminocyclopropane-1-carboxylate oxidase and DPE. This knowledge of the mechanisms that regulate starch and sugar metabolisms during maturation and ripening is fundamental to determine the harvest moment, reduce postharvest losses and improve final product quality of breeding programs.


title: Trial-by-trial fluctuations in amygdala activity track motivational enhancement of desirable sensory evidence during perceptual decision-making

abstract: People are biased towards seeing outcomes that they are motivated to see. For example, sports fans often perceive the same ambiguous foul in favor of the team they support. Here, we test the hypothesis that motivational biases in perceptual decision-making arise from amygdala-dependent biases in sensory processing. Human participants were rewarded for correctly categorizing an ambiguous image into one of two categories while undergoing fMRI. On each trial, we used a financial bonus to motivate participants to see one category over another. The reward maximizing strategy was to perform the categorizations accurately, but participants were biased towards categorizing the images as the category we motivated them to see. Heightened amygdala activity was associated with motivation consistent categorizations, and tracked trial-by-trial enhancement of neural activity in sensory cortices that was specific to the desirable category. Analyses using a drift diffusion model provide converging evidence that trial-by-trial amygdala activity was associated with stronger biases in the accumulation of sensory evidence. Prior work examining biases in perceptual decision-making have focused on the role of frontoparietal regions. Our work highlights an important contribution of the amygdala. When people are motivated to see one outcome over another, the amygdala biases perceptual decisions towards those outcomes.


title: The Direct Subjective Refraction: Unsupervised measurements of subjective refraction using defocus waves

abstract: We present the Direct Subjective Refraction (DSR), a new subjective refraction method, and validate it vs the Traditional Subjective Refraction (TSR) and an unsupervised version of it (UTSR). We project an optotunable lens onto the eye to create Temporal Defocus Waves produces flicker and chromatic distortions, minimum when the mean optical power of the wave matches the spherical equivalent of the eye. 25 subjects performed the DSR visual and UTSR tasks without supervision. DSR is more repeatable than TSR and UTSR (standard deviations {+/-}0.17D, {+/-}0.28, and {+/-}0.47D). The time per repetition of DSR is only 39s (almost 6 min for TSR). Cyclopegia severely affects UTSR, but not DSR, confirming that the DSR task de-activates the accommodative system. DSR is a new method to obtain the spherical equivalent that does not requires supervision and overpasses existing subjective methods in terms of accuracy, precision, and measurement time.


title: Cortical tracking of voice pitch in the presence of multiple speakers depends on selective attention

abstract: Voice pitch carries linguistic as well as non-linguistic information. Previous studies have described cortical tracking of voice pitch in clean speech, with responses reflecting both pitch strength and pitch value. However, pitch is also a powerful cue for auditory stream segregation, especially when competing streams have pitch differing in fundamental frequency, as is the case when multiple speakers talk simultaneously. We therefore investigated how cortical speech pitch tracking is affected in the presence of a second, task-irrelevant speaker. We analyzed human magnetoencephalography (MEG) responses to continuous narrative speech, presented either as a single talker in a quiet background, or as a two-talker mixture of a male and a female speaker. In clean speech, voice pitch was associated with a right-dominant response, peaking at a latency of around 100 ms, consistent with previous EEG and ECoG results. The response tracked both the presence of pitch as well as the relative value of the speakers fundamental frequency. In the two-talker mixture, pitch of the attended speaker was tracked bilaterally, regardless of whether or not there was simultaneously present pitch in the speech of the irrelevant speaker. Pitch tracking for the irrelevant speaker was reduced: only the right hemisphere still significantly tracked pitch of the unattended speaker, and only during intervals in which no pitch was present in the attended talkers speech. Taken together, these results suggest that pitch-based segregation of multiple speakers, at least as measured by macroscopic cortical tracking, is not entirely automatic but strongly dependent on selective attention.


title: Harmonizing Functional Connectivity Reduces Scanner Effects in Community Detection

abstract: Community detection on graphs constructed from functional magnetic resonance imaging (fMRI) data has led to important insights into brain functional organization. Large studies of brain community structure often include images acquired on multiple scanners across different studies. Differences in scanner can introduce variability into the downstream results, and these differences are often referred to as scanner effects. Such effects have been previously shown to significantly impact common network metrics. In this study, we identify scanner effects in data-driven community detection results and related network metrics. We assess a commonly employed harmonization method and propose new methodology for harmonizing functional connectivity that leverage existing knowledge about network structure as well as patterns of covariance in the data. Finally, we demonstrate that our new methods reduce scanner effects in community structure and network metrics. Our results highlight scanner effects in studies of brain functional organization and provide additional tools to address these unwanted effects. These findings and methods can be incorporated into future functional connectivity studies, potentially preventing spurious findings and improving reliability of results.


title: Brain-wide neural co-activations in resting human

abstract: Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of <0.1Hz. However, fast brain-wide networks at the timescales of neuronal events (milliseconds to sub-seconds) and their spatial, spectral, and propagational characteristics remain unclear due to the temporal constraints of hemodynamic signals. With milli-second resolution and whole-head coverage, scalp-based electroencephalography (EEG) provides a unique window into brain-wide networks with neuronal-timescale dynamics, shedding light on the organizing principles of brain function. Using state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs). These cCAPs revealed brain-wide intrinsic networks and their dynamics, indicating the configuration/reconfiguration of resting human brains into recurring and propagating functional states, which are featured with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations. Rich oscillational structures across a wide frequency band (i.e., 0.6Hz, 5Hz, and 10Hz) were embedded in the dynamics of these functional states. We further identified a superstructure that regulated between-state propagations and governed a significant aspect of brain-wide network dynamics. These findings demonstrated how resting-state EEG data can be functionally decomposed using cCAPs to reveal rich structures of brain-wide human neural activations.


title: Modulating effects of FGF12 variants on NaV1.2 and NaV1.6 associated with Developmental and Epileptic Encephalopathy and Autism Spectrum Disorder

abstract:
ObjectiveFibroblast growth factor 12 (FGF12) may represent an important modulator of neuronal network activity and has been associated with developmental and epileptic encephalopathy (DEE). We sought to identify the underlying pathomechanism of FGF12-related disorders.

MethodsPatients with pathogenic variants in FGF12 were identified through published case reports, GeneMatcher and whole exome sequencing of own case collections. The functional consequences of two missense variants and two copy number variants (CNVs) were studied by co-expression of wild-type and mutant FGF12 in neuronal-like cells (ND7/23) with the sodium channels NaV1.2 or NaV1.6, including their functional active beta-1 and beta-2 sodium channel subunits (SCN1B and SCN2B).

ResultsFour variants in FGF12 were identified for functional analysis: one novel FGF12 variant in a patient with autism spectrum disorder and three variants from previously published patients affected by developmental and epileptic encephalopathy (DEE). We demonstrate the differential regulating effects of wildtype and mutant FGF12 on NaV1.2 and NaV1.6 channels. Here, FGF12 variants lead to a complex kinetic influence on Nav1.2 and Nav 1.6, including loss- as well as gain-of function changes in fast inactivation as well as loss-of function changes in slow inactivation.

InterpretationFor the first time, we could demonstrate the detailed regulating effect of FGF12 on NaV1.2 and NaV1.6 and confirmed the complex effect of FGF12 on neuronal network activity. Our findings expand the phenotypic spectrum related to FGF12 variants and elucidate the underlying pathomechanism. Specific variants in FGF12-associated disorders may be amenable to precision treatment with sodium channel blockers.


title: Redox regulation of PTPN22 affects the severity of T cell dependent autoimmune inflammation

abstract:
Chronic autoimmune diseases are associated with mutations in PTPN22, a modifier of T cell receptor signaling. As with all protein tyrosine phosphatases the activity of PTPN22 is redox regulated, but if or how such regulation can modulate inflammatory pathways in vivo is not known. To determine this, we created a mouse with a cysteine-to-serine mutation at position 129 in PTPN22 (C129S), a residue proposed to alter the redox regulatory properties of PTPN22 by forming a disulfide with the catalytic C227 residue. The C129S mutant mouse showed a stronger T cell-dependent inflammatory response and development of T cell dependent autoimmune arthritis due to enhanced TCR signaling and activation of T cells, an effect neutralized by a mutation in Ncf1, a component of the NOX2 complex. Activity assays with purified proteins suggest that the functional results can be explained by an increased sensitivity to oxidation of the C129S mutated PTPN22 protein. We also observed that the disulfide of native PTPN22 can be directly reduced by the thioredoxin system, while the C129S mutant lacking this disulfide was less amenable to reductive reactivation. In conclusion, we show that PTPN22 functionally interacts with Ncf1 and is regulated by oxidation via the non-catalytic C129 residue and oxidation-prone PTPN22 leads to increased severity in the development of T cell-dependent autoimmunity.

Significance statementA hitherto unstudied aspect of PTPN22 biology is its regulation by cell redox states. Here we created a mouse model where PTPN22 was mutated to respond differentially to redox levels in vivo and found that PTPN22 function is regulated by reactive oxygen species and that redox regulation of PTPN22 impacts T-cell-dependent autoimmune inflammation.

category: immunology


title: Horizontal gene transfer in 44 early diverging fungi favors short, metabolic, extracellular proteins from associated bacteria

abstract:
Numerous studies have been devoted to individual cases of horizontally acquired genes in fungi. It has been shown that such genes expand their metabolic capabilities and contribute to their adaptations as parasites or symbionts. Some studies have provided a more extensive characterization of the horizontal gene transfer (HGT) in Dikarya. However, in the early diverging fungi (EDF), the overall influence of HGT on the ecological adaptation and evolution is largely unknown. In order to fill this gap, we have designed a computational pipeline to obtain a sample of over 600 phylogenetic trees with evidence for recent to moderately old HGT across multiple EDF genomes ranging from Chytridiomycota and Blastocladiomycota to Mucoromycota. Our pipeline is designed to obtain a small sample of reliable HGT events with a possibly minimal number of false detections that distort the overall statistical patterns. We show that transfer rates differ greatly between closely related species and strains, but the ancestrally aquatic fungi are generally more likely to acquire foreign genetic material than terrestrial ones. A close ecological relationship with another organism is a predisposing condition, but does not always result in an extensive gene exchange, with some fungal lineages showing a preference for HGT from loosely associated soil bacteria.

ImportanceAlthough it is now recognized that horizontal gene exchange is a factor influencing the adaptation and evolution of eukaryotic organisms, the so far described cases in early diverging fungi (EDF) are fragmentary, and a large-scale comprehensive study is lacking. We have designed a methodology to obtain a reliable, statistical sample of inter-kingdom xenologs across the tree of life of EDF to give a preliminary characterization of their general properties and patterns. We study how different fungal lineages vary in terms of the number of xenologs, what are their ecological associations, and the molecular properties of proteins encoded by the acquired genes. Our results help to better understand to what extent and in what way the incorporation of foreign genetic material shaped the present biodiversity of fungi.

category: genomics


title: A Non-Negative Matrix Tri-Factorization based Method for Predicting Antitumor Drug Sensitivity

abstract: Large annotated cell line collections have been proven to enable the prediction of drug response in the preclinical setting. We present an enhancement of Non-Negative Matrix Tri-Factorization method, which allows the integration of different data types for the prediction of missing associations. To test our method we retrieved a dataset from CCLE, containing the connections among cell lines and drugs by means of their IC50 values. We performed two different kind of experiments: a) prediction of missing values in the matrix, b) prediction of the complete drug profile of a new cell line, demonstrating the validity of the method in both scenarios.


title: TRAWLING: a Transcriptome Reference Aware of spLIciNG events.

abstract:
Alternative splicing is critical for human gene expression regulation and plays an important role in multiple human diseases. In this context, RNA sequencing has emerged as powerful approach to detect alternative splicing events.

In parallel, fast alignment-free methods have emerged as a viable alternative to quantify gene and transcript level abundance from RNAseq data. However, the ability to detect differential splicing events is dependent on the annotation of the transcript reference provided by the user.

Here, we introduce a new reference transcriptome aware of splicing events, TRAWLING, which simplifies the detection of aberrant splicing events in a fast and simple way. In addition, we evaluate the performances and the benefits of aligning transcriptome data to TRAWLING using three different RNA sequencing datasets: whole transcriptome sequencing, single cell RNA sequencing and Digital RNA with pertUrbation of Genes.

Collectively, our comprehensive evaluation underlines the value of using TRAWLING in transcriptomic data analysis.

Availability and implementationOur code is available at https://github.com/Novartis/TRAWLING


title: TRAWLING: a Transcriptome Reference AWare of spLIciNG events.


title: A Leak-Free Head-Out Plethysmography System to Accurately Assess Lung Function in Mice

abstract:
Mice are a valuable model for elegant studies of complex, systems-dependent diseases, including pulmonary diseases. Current tools to assess lung function in mice are either terminal or lack accuracy. We set out to develop a low-cost, accurate, head-out variable-pressure plethysmography system to allow for repeated, non-terminal measurements of lung function in mice. Current head-out plethysmography systems are limited by air leaks that prevent accurate measures of volume and flow. We designed an inflatable cuff that encompasses the mouses neck preventing air leak. We wrote corresponding software to collect and analyze the data, remove movement artifacts, and automatically calibrate each dataset. This software calculates inspiratory/expiratory volume, inspiratory/expiratory time, breaths per minute, enhanced pause, mid-expiratory flow, and end-inspiratory pause. To validate the use, we established our plethysmography system accurately measured tidal breathing, the bronchoconstrictive response to methacholine, sex and age associated changes in breathing, and breathing changes associated with house dust mite sensitization. Our estimates of volume, flow, and timing of breaths are in line with published estimates, we observed dose-dependent decreases in volume and flow in response to methacholine (P < 0.05), increased lung volume and decreased breathing rate with aging (P < 0.05), and that house dust mite sensitization decreased tidal volume and flow (P <0.05) while exacerbating the methacholine induced increases in inspiratory and expiratory time (P < 0.05). We describe an accurate, sensitive, low-cost, head-out plethysmography system that allows for longitudinal studies of pulmonary disease in mice.

New & NoteworthyWe describe a variable-pressure head-out plethysmography system that can be used to assess lung function in mice. A balloon cuff that inflates around the mouses neck prevents air leak, allowing for accurate measurements of lung volume and air flow. Custom software facilitates system calibration, removes movement artifacts, and eases data analysis. The system was validated by measuring tidal breathing, responses to methacholine, and changes associated with house dust mite sensitization, sex, and aging.

Contributions to StudyO_LIStephanie Bruggink: development of head-out plethysmography chamber, measurement of breathing, data analysis, prepared manuscript
C_LIO_LIKyle Kentch: development of head-out plethysmography chamber, programmed software to collect and analyze data, prepared manuscript
C_LIO_LIJason Kronenfeld: development of tools to analyze data, analysis of data
C_LIO_LIBenjamin Renquist: development of head-out plethysmography chamber, statistical analysis, prepared manuscript
C_LI

category: physiology


title: Finger stability in precision grips

abstract: Stable precision grips using the fingertips are a cornerstone of human hand dexterity. Occasionally, however, our fingers become unstable and snap into a hyper-extended posture. This is because multi-link mechanisms, like our fingers, can buckle under tip forces. Suppressing this instability is crucial for hand dexterity, but how the neuromuscular system does so is unknown. Here we show that finger stability is due to the stiffness from muscle contraction and likely not feedback control. We recorded maximal force application with the index finger and found that most buckling events lasted less than 50ms, too fast for sensorimotor feedback to act. However, a biomechanical model of the finger predicted that muscle-induced stiffness is also insufficient for stability at maximal force unless we add springs to stiffen the joints. We tested this prediction in 39 volunteers. Upon adding stiffness, maximal force increased by 34{+/-}3%, and muscle electromyography readings were 21{+/-}3% higher for the finger flexors (mean{+/-}standard error). Hence, people refrain from applying truly maximal force unless an external stabilizing stiffness allows their muscles to apply higher force without losing stability. Muscle recordings and mathematical modeling show that the splint offloads the demand for muscle co-contraction and this reduced co-contraction with the splint underlies the increase in force. But more stiffness is not always better. Stiff fingers would interfere the ability to passively adapt to complex object geometries and precisely regulate force. Thus, our results show how hand function arises from neurally tuned muscle stiffness that balances finger stability with compliance.


title: Why do hippocampal mossy cells matter? It depends on the frequency and context.

abstract:
The discrimination of similar episodes and places, and their representation as distinct memories, depend on a process called pattern separation that relies on the circuitry of the hippocampal dentate gyrus (DG). Mossy cells (MCs) are key neurons in the circuitry, but how they influence DG network dynamics, function, and seizure risk has not been fully elucidated. We found the net impact of MCs was inhibitory at physiological frequencies connected with learning and behaviour, and their absence associated with deficits in pattern separation and spatial memory; at higher frequencies, their net impact was excitatory, and their absence protected against seizures. Thus, MCs influence DG outputs in a highly dynamic manner that varies with frequency and context.

One-Sentence SummaryHippocampal mossy cells are required for learning and memory; but their absence protects against seizures.


title: Evaluating the role of coevolution in a horizontally transmitted mutualism

abstract: Mutualism depends on the alignment of host and symbiont fitness. Horizontal transmission can readily decouple fitness interests, yet horizontally transmitted mutualisms are common in nature. We hypothesized that pairwise coevolution and specialization in host-symbiont interactions underlies the maintenance of cooperation in a horizontally transmitted mutualism. Alternatively, we predicted selection by multiple host species may select for cooperative traits in a generalist symbiont through diffuse coevolution. We tested for signatures of pairwise coevolutionary change between the squash bug Anasa tristis and its horizontally acquired bacterial symbiont Caballeronia spp. by measuring local adaptation. We found no evidence for local adaptation between sympatric combinations of A. tristis squash bugs and Caballeronia spp. across their native geographic range. To test for diffuse coevolution, we performed reciprocal inoculations to test for specialization between three Anasa host species and Caballeronia spp. symbionts isolated from conspecific hosts. We observed no evidence of specialization across host species. Our results demonstrate generalist dynamics underlie the interaction between Anasa insect hosts and their Caballeronia spp. symbionts. Specifically, diffuse coevolution between multiple host species with a shared generalist symbiont may maintain cooperative traits despite horizontal transmission.


title: Profiling of the drug resistance of thousands of Src tyrosine kinase mutants uncovers a regulatory network that couples autoinhibition to the dynamics of the catalytic domain

abstract: Protein kinase inhibitors are effective cancer therapies, but acquired resistance often limits clinical efficacy. Despite the cataloguing of numerous resistance mutations with model studies and in the clinic, we still lack a comprehensive understanding of kinase inhibitor resistance. Here, we measured the resistance of thousands of Src tyrosine kinase mutants to a panel of ATP-competitive inhibitors. We found that ATP-competitive inhibitor resistance mutations are distributed throughout Srcs catalytic domain. In addition to inhibitor contact residues, residues that participate in regulating Srcs phosphotransferase activity were prone to the development of resistance. Unexpectedly, a resistance-prone cluster of residues that are on the top face of the N-terminal lobe of the catalytic domain contributes to Src autoinhibition by reducing the dynamics of the catalytic domain, and mutations in this cluster led to resistance by lowering inhibitor affinity and promoting kinase hyperactivation. Together, our studies demonstrate how comprehensive profiling of drug resistance can be used to understand potential resistance pathways and uncover new mechanisms of kinase regulation.

category: biochemistry


title: HLAncPred: A method for predicting promiscuous non-classical HLA binding sites

abstract:
In the last two decades, ample of methods have been developed to predict the classical HLA binders in an antigen. In contrast, limited attempts have been made to develop methods for predicting binders for non-classical HLA; due to the scarcity of sufficient experimental data and lack of community interest. Of Note, non-classical HLA plays a crucial immunomodulatory role and regulates various immune responses. Recent studies revealed that non-classical HLA (HLA-E & HLA-G) based immunotherapies have many advantages over classical HLA based-immunotherapy, particularly against COVID-19. In order to facilitate the scientific community, we have developed an artificial intelligence-based method for predicting binders of non-classical HLA alleles (HLA-G and HLA-E). All the models were trained and tested on experimentally validated data obtained from the recent release of IEDB. The machine learning based-models achieved more than 0.98 AUC for HLA-G alleles on validation or independent dataset. Similarly, our models achieved the highest AUC of 0.96 and 0.88 on the validation dataset for HLA-E*01:01, HLA-E*01:03, respectively. We have summarized the models developed in the past for non-classical HLA binders and compared with the models developed in this study. Moreover, we have also predicted the non-classical HLA binders in the spike protein of different variants of virus causing COVID-19 including omicron (B.1.1.529) to facilitate the community. One of the major challenges in the field of immunotherapy is to identify the promiscuous binders or antigenic regions that can bind to a large number of HLA alleles. In order to predict the promiscuous binders for the non-classical HLA alleles, we developed a web server HLAncPred (https://webs.iiitd.edu.in/raghava/hlancpred), and a standalone package.

Key PointsO_LINon-classical HLAs play immunomodulatory roles in the immune system.
C_LIO_LIHLA-E restricted T-cell therapy may reduce COVID-19 associated cytokine storm.
C_LIO_LIIn silico models developed for predicting binders for HLA-G and HLA-E.
C_LIO_LIIdentification of non-classical HLA binders in strains of coronavirus
C_LIO_LIA webserver for predicting promiscuous binders for non-classical HLA alleles
C_LI

Authors BiographyO_LIAnjali Dhall is currently working as Ph.D. in Bioinformatics from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
C_LIO_LISumeet Patiyal is currently working as Ph.D. in Bioinformatics from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
C_LIO_LIGajendra P. S. Raghava is currently working as Professor and Head of Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
C_LI

category: bioinformatics


title: Seipin transmembrane segments critically function in triglyceride nucleation and lipid droplet budding from the membrane

abstract: Lipid droplets (LDs) are organelles formed in the endoplasmic reticulum (ER) to store triacylglycerol (TG) and sterol esters. The ER protein seipin is key for LD biogenesis. Seipin forms a cage-like structure, with each seipin monomer containing a conserved hydrophobic helix (HH) and two transmembrane (TM) segments. How the different parts of seipin function in TG nucleation and LD budding is poorly understood. Here, we utilized molecular dynamics simulations of human seipin, along with cell-based experiments, to study seipins functions in protein-lipid interactions, lipid diffusion, and LD maturation. All-atom (AA) simulations indicate that most seipin TM segment residues located in the phospholipid (PL) tail region of the bilayer attract TG. We also find seipin TM segments control lipid diffusion and permeation into the protein complex. Simulating larger, growing LDs with coarse-grained (CG) models, we find that the seipin TM segments form a constricted neck structure to facilitate conversion of a flat oil lens into a budding LD. Using cell experiments and simulations, we also show that conserved, positively charged residues at the end of seipins TM segments affect LD maturation. We propose a model in which seipin TM segments critically function in TG nucleation and LD growth.

category: biophysics


abstract:
The weighted ensemble (WE) family of methods is one of several statistical-mechanics based path sampling strategies that can provide estimates of key observables (rate constants, pathways) using a fraction of the time required by direct simulation methods such as molecular dynamics or discrete-state stochastic algorithms. WE methods oversee numerous parallel trajectories using intermittent overhead operations at fixed time intervals, enabling facile interoperability with any dynamics engine. Here, we report on major upgrades to the WESTPA software package, an open-source, high-performance framework that implements both basic and recently developed WE methods. These upgrades offer substantial improvements over traditional WE. Key features of the new WESTPA 2.0 software enhance efficiency and ease of use: an adaptive binning scheme for more efficient surmounting of large free energy barriers, streamlined handling of large simulation datasets, exponentially improved analysis of kinetics, and developer-friendly tools for creating new WE methods, including a Python API and resampler module for implementing both binned and "binless" WE strategies.

Table of Contents/Abstract ImageFor the manuscript "WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications" by Russo et al.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/471280v2_ufig1.gif" ALT="Figure 1">
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title: WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications


title: Effects of stimulus pulse rate on somatosensory adaptation in the human cortex

abstract:
BackgroundIntracortical microstimulation (ICMS) of the somatosensory cortex can restore sensation to people with neurological diseases. However, many aspects of ICMS are poorly understood, including the effect of continuous stimulation on percept intensity over time.

ObjectiveHere, we evaluate how tactile percepts, evoked by ICMS in the somatosensory cortex of a human participant adapt over time.

MethodsWe delivered continuous and intermittent ICMS to the somatosensory cortex and assessed the reported intensity of tactile percepts over time in a human participant. Experiments were conducted across approximately one year and linear mixed effects models were used to assess significance.

ResultsContinuous stimulation at high frequencies led to rapid decreases in intensity, while low frequency stimulation maintained percept intensity for longer periods. Burst-modulated stimulation extended the time before the intensity began to decrease, but all protocols ultimately resulted in complete sensation loss within one minute. Intermittent stimulation paradigms with several seconds between stimulus trains also led to decreases in intensity on many electrodes, but never resulted in extinction of sensation after over three minutes of stimulation. Additionally, longer breaks between each pulse train resulted in some recovery of the stimulus-evoked percepts. For several electrodes, intermittent stimulation had almost no effect on the perceived intensity.

ConclusionsIntermittent ICMS paradigms were more effective at maintaining percepts, and given that transient activity in the somatosensory cortex dominates the response to object contact, this stimulation method may mimic natural cortical activity and improve the perception of stimulation over time.


title: Role of oxidation of excitation-contraction coupling machinery in age-dependent loss of muscle function in C. elegans

abstract: Age-dependent loss of body wall muscle function and impaired locomotion occur within 2 weeks in C. elegans; however, the underlying mechanism has not been fully elucidated. In humans, age-dependent loss of muscle function occurs at about 80 years of age and has been linked to dysfunction of ryanodine receptor (RyR)/intracellular calcium (Ca2+) release channels on the sarcoplasmic reticulum (SR). Mammalian skeletal muscle RyR1 channels undergo age-related remodeling due to oxidative overload, leading to loss of the stabilizing subunit calstabin1 (FKBP12) from the channel macromolecular complex. This destabilizes the closed state of the channel resulting in intracellular Ca2+ leak, reduced muscle function, and impaired exercise capacity. We now show that the C. elegans RyR homolog, UNC-68, exhibits a remarkable degree of evolutionary conservation with mammalian RyR channels and similar age-dependent dysfunction. Like RyR1 in mammals UNC-68 encodes a protein that comprises a macromolecular complex which includes the calstabin1 homolog FKB-2 and is immunoreactive with antibodies raised against the RyR1 complex. Further, as in aged mammals, UNC-68 is oxidized and depleted of FKB-2 in an age-dependent manner, resulting in "leaky" channels, depleted SR Ca2+ stores, reduced body wall muscle Ca2+ transients, and age-dependent muscle weakness. FKB-2 (ok3007)-deficient worms exhibit reduced exercise capacity. Pharmacologically induced oxidization of UNC-68 and depletion of FKB-2 from the channel independently caused reduced body wall muscle Ca2+ transients. Preventing FKB-2 depletion from the UNC-68 macromolecular complex using the Rycal drug S107 improved muscle Ca2+ transients and function. Taken together, these data suggest that UNC-68 oxidation plays a role in age-dependent loss of muscle function. Remarkably, this age-dependent loss of muscle function induced by oxidative overload, which takes ~2 years in mice and ~80 years in humans, occurs in less than 2-3 weeks in C. elegans, suggesting that reduced anti-oxidant capacity may contribute to the differences in life span amongst species.


title: Barrier mitigation measures trigger the rapid recovery of genetic connectivity in five freshwater fish species

abstract:
Rivers are heavily fragmented by man-made instream barriers such as dams and weirs. This hyper-fragmentation is a major threat to freshwater biodiversity and restoration policies are now adopted worldwide to mitigate these impacts. However, there is surprisingly little feedback on the efficiency of barrier mitigation measures in restoring riverine connectivity, notably for non-migratory fish species. Here, we implemented a "before-after genetic monitoring" of the restoration of 11 weirs in France using a dedicated genetic index of fragmentation (the FINDEX), with a focus on five fish species from two genera. We found that most obstacles actually had a significant impact on connectivity before restoration, especially the highest and steepest ones, with an overall barrier effect of about 51% of the maximal theoretical impact. Most importantly, we demonstrated for the first time that mitigation measures such as dam removal or fish pass creation significantly and rapidly improved connectivity, with -for some barriers-a complete recovery of the genetic connectivity in less than twelve months. Our study provides a unique and strong proof-of-concept that barrier removal is an efficient strategy to restore riverine connectivity and that molecular tools can provide accurate measures of restoration efficiency within a few months.

Graphical Abstract

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title: Modeling implanted metals in electrical stimulation applications

abstract:
BackgroundMetal implants impact the dosimetry assessment in electrical stimulation techniques. Therefore, they need to be included in numerical models. While currents in the body are ionic, metals only allow electron transport. In fact, charge transfer between tissues and metals requires electric fields to drive the electrochemical reactions at the interface. Thus, metal implants may act as insulators or as conductors depending on the scenario.

Objective/HypothesisThe aim of this paper is to provide a theoretical argument that guides the choice of the correct representation of metal implants using purely electrical models but considering the electrochemical nature of the problem in the technology of interest.

MethodsWe built a simple model of a metal implant exposed to a homogeneous electric field of various magnitudes to represent both weak (e.g., tDCS), medium (TMS) or strong field stimulation. The same geometry was solved using two different models: a purely electric one (with different conductivities for the implant), and an electrochemical one. As an example of application, we also modeled a transcranial electrical stimulation (tES) treatment in a realistic head model with a skull plate using a high and low conductivity value for the plate.

ResultsMetal implants generally act as electric insulators when exposed to electric fields up to around 100 V/m (tES and TMS range) and they only resemble a perfect conductor for fields in the order of 1000 V/m and above. The results are independent of the implants metal, but they depend on its geometry.

Conclusion(s)Metal implants can be accurately represented by a simple electrical model of constant conductivity, but an incorrect model choice can lead to large errors in the dosimetry assessment. In particular, tES modeling with implants incorrectly treated as conductors can lead to errors of 50% in induced fields or more. Our results can be used as a guide to select the correct model in each scenario.

category: bioengineering


title: Kinetic frustration by limited bond availability controls the LAT protein condensation phase transition on membranes

abstract: LAT is a membrane-linked scaffold protein that undergoes a phase transition to form a two-dimensional protein condensate on the membrane during T cell activation. Governed by tyrosine phosphorylation, LAT recruits various proteins that ultimately enable condensation through a percolation network of discrete and selective protein-protein interactions. Here we describe detailed kinetic measurements of the phase transition, along with coarse-grained model simulations, that reveal LAT condensation is kinetically frustrated by the availability of bonds to form the network. Unlike typical miscibility transitions in which compact domains may coexist at equilibrium, the LAT condensates are dynamically arrested in extended states, kinetically trapped out of equilibrium. Modeling identifies the structural basis for this kinetic arrest as the formation of spindle arrangements, favored by limited multivalent binding interactions along the flexible, intrinsically disordered LAT protein. These results reveal how local factors controlling the kinetics of LAT condensation enable formation of different, stable condensates, which may ultimately coexist within the cell.


title: Metabolic profiling of serum for osteoarthritis biomarkers

abstract: Osteoarthritis is a prevalent aging disease in the world, and in recent years it has shown a trend toward younger age, which is becoming a major health problem in the world and seriously endangers the health of the elderly. However, the etiology and pathogenesis of osteoarthritis are still unclear, causing great trouble for treatment. To screen out potential biomarkers that could be used as identification of osteoarthritis and explore the pathogenesis of osteoarthritis, we performed untargeted metabolomics analysis of nine New Zealand rabbit serum samples by LC-MS / MS, including three normal serum samples (control group) and six osteoarthritis serum samples (case group). Finally 44 differential metabolites were identified, and the ROC analysis results indicated that a total of 36 differential metabolites could be used as potential biomarkers. Further metabolic pathway enrichment analysis was performed on these differential metabolites, and we found that a total of 17 metabolic pathways were affected, which may provide directions for the study of osteoarthritis mechanisms.


title: LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung

abstract: An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a broad-spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease and drug treatment. These atlases are provided as independent and integrated queriable datasets, with an emphasis on dynamic visualization, figure generation and reference-based classification of user-provided datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, data portals and datasets from LungMAP and external research efforts.


title: Cryptic local adaptation is pervasive across environmental and evolutionary gradients

abstract: Cryptic local adaptation--where an environmental effect masks the magnitude of the genetic contribution to a phenotype--has long been a topic of interest in ecology and evolution. Here, we systematically document the magnitude and drivers of two common forms of cryptic local adaptation--counter- and cogradient variation. Using a hierarchical Bayesian meta-analysis, we calculated the overall effect size as 1.03 for countergradient variation and 0.90 for cogradient variation. This result indicates that the genetic effect of cryptic local adaptation is approximately equal to a one standard deviation change in trait value between the most disparate populations. We also found that the abiotic and biotic covariates with the largest mean effects were temperature (2.50) and gamete size (2.78), although there was substantial variance. Our results demonstrate the pervasiveness and large effect of cryptic local adaptation in wild populations and underscores the importance of accounting for these effects in future studies.


title: Relationships between pond water and tilapia skin microbiomes in aquaculture ponds in Malawi

abstract:
Intensification of fish farming practices is being driven by the demand for increased food production to support a rapidly growing global human population, particularly in lower-middle income countries. Intensification of production, however, increases the risk of disease outbreaks and thus likelihood for crop losses. The microbial communities that colonise the skin mucosal surface of fish are poorly understood, but are important in maintaining fish health and resistance against disease. This skin microbial community is susceptible to disruption through stressors associated with transport, handling and the environment of intensive practices, and this risks the propagation of disease-causing pathogens. In this study, we characterised the microbial assemblages found on tilapia skin -- the most widely farmed finfish globally -- and in the surrounding water of seven earthen aquaculture ponds from two pond systems in distinct geographic regions in Malawi. Metabarcoding approaches were used to sequence the prokaryotic and microeukaryotic communities. We found 92% of prokaryotic amplicon sequence variants were common to both skin and water samples. Differentially enriched and core taxa, however, differed between the skin and water samples. In tilapia skin, Cetobacterium, Paucibacter, Pseudomonas and Comamonadaceae were enriched, whereas, the cyanobacteria Cyanobium, Microcystis and/or Synechocystis, and the diatom Cyclotella, were most prevalent in pond water. Ponds that clustered together according to their water prokaryotic communities also had similar microeukaryotic communities indicating strong environmental influences on prokaryotic and microeukaryotic community structures. While strong site-specific clustering was observed in pond water, the grouping of tilapia skin prokaryotes by pond site was less distinct, suggesting fish microbiota have a greater buffering capacity against environmental influences. The characterised diversity, structure and variance of microbial communities associated with tilapia culture in Malawi provides the baseline for studies on how future intensification practices may lead to microbial dysbiosis and disease onset.

HighlightsO_LITilapia skin communities vary in different ponds but share some common taxa
C_LIO_LIPond sites have a stronger influence on water microbiome community structure than in fish skin
C_LIO_LISelected skin-associated taxa could be used to monitor dysbiotic events
C_LIO_LIThe fish skin microeukaryotic community is complex and poorly characterised
C_LI


title: Chronic kidney disease alters Pin1 phosphorylation and parathyroid hormone mRNA binding proteins leading to secondary hyperparathyroidism

abstract: Parathyroid hormone (PTH) regulates calcium metabolism and bone strength. Chronic kidney disease leads to secondary hyperparathyroidism (SHP) which increases morbidity and mortality. In experimental SHP, the increased PTH gene expression is due to enhanced PTH mRNA stability, mediated by changes in its interaction with stabilizing AUF1 and destabilizing KSRP. Pin1 isomerizes target proteins and leads to KSRP dephosphorylation. In SHP, Pin1 isomerase activity is decreased and phosphorylated KSRP fails to bind PTH mRNA, resulting in high PTH mRNA stability and levels. However, the up- and down-stream mechanisms by which kidney failure stimulates the parathyroid remain elusive. We now reveal a pathway where kidney failure induces parathyroid Pin1 phosphorylation, linking Pin1, KSRP and PTH mRNA stability as key players for the high PTH expression in SHP. We identified by mass-spectrometry, changes in rat parathyroid proteome and phosphoproteome profiles induced by impaired renal function, including KSRP phosphorylation at Pin1 target sites. Furthermore, both acute and chronic kidney failure led to parathyroid-specific Pin1 Ser16 and Ser71 phosphorylation, which disrupts Pin1 activity. Accordingly, pharmacologic Pin1 inhibition, that mimics the decreased Pin1 activity in SHP, increased PTH expression ex-vivo in parathyroid organ cultures and in transfected cells, through the PTH mRNA protein-interacting element and KSRP phosphorylation at potential Pin1-binding motifs. Therefore, kidney failure leads to loss of parathyroid Pin1 activity by inducing Pin1 phosphorylation. This predisposes parathyroids to increase PTH production through impaired PTH mRNA decay that is dependent on KSRP phosphorylation. Pin1 and KSRP phosphorylation and the Pin1-KSRP-PTH mRNA axis thus drive SHP.


title: Kidney failure alters parathyroid Pin1 phosphorylation and parathyroid hormone mRNA binding proteins leading to secondary hyperparathyroidism