title: Sexual conflict drives micro- and macroevolution of sexual dimorphism in immunity

abstract:
BackgroundSexual selection can have major effects on mating rates and sex-specific costs of mating and may thereby influence sex-differences in immunity as well as associated host-pathogen dynamics. Yet, experimental evidence linking the mating system to evolved sexual dimorphism in immunity are scarce and the direct effects of mating rate on immunity are not well established. Here, we use transcriptomic analyses, experimental evolution and phylogenetic comparative methods to study the association between the mating system and sexual dimorphism in immunity in seed beetles, where mating causes internal injuries in females.

ResultsWe demonstrate that female phenoloxidase (PO) activity, involved in wound healing and defence against parasitic infections, is elevated relative to males. This difference is accompanied by concomitant sex-differences in the expression of genes in the pro-phenoloxidase activating cascade. We document substantial phenotypic plasticity in female PO activity in response to mating and show that experimental evolution under enforced monogamy (resulting in low remating rates and sexual conflict relative to natural polygamy) rapidly decreases female (but not male) PO activity. Moreover, monogamous females have evolved increased tolerance to bacterial infection unrelated to mating, implying that female responses to costly mating may trade off with other aspects of immune defence, an hypothesis which broadly accords with the documented sex differences in gene expression. Finally, female (but not male) PO activity shows correlated evolution with the perceived harmfulness of male genitalia across 12 species of seed beetles, suggesting that sexual conflict has a significant influence on sexual dimorphisms in immunity in this group of insects.

ConclusionsOur study provides insights into the links between sexual conflict and sexual dimorphism in immunity at the molecular and phenotypic level and suggests that selection pressures moulded by mating interactions can lead to a sex-specific mosaic of immune responses with important implications for host-pathogen dynamics in sexually reproducing organisms.


title: Comprehensive analysis of hsa-miR-654-5p's tumor-suppressing functions

abstract:
The pivotal roles of miRNAs in carcinogenesis, metastasis, and prognosis have been demonstrated recently in various cancers. This study intended to investigate the specific roles of hsa-miR-654-5p in lung cancer, which was poorly discussed. A series of closed-loop bioinformatic functional analyses were integrated with in vitro experimental validation to explore the overall biological functions and pan-cancer regulation pattern of miR-654-5p. We found that miR-654-5p abundance was significantly elevated in LUAD tissues and correlated with patients survival. 275 potential targets of miR-654-5p were then identified and the miR-654-5p-RNF8 regulation axis was validated in vitro as a proof of concept. Furthermore, we revealed the tumor-suppressing roles of miR-654-5p and demonstrated that miR-654-5p inhibited lung cancer cell epithelial-mesenchymal transition (EMT) process, cell proliferation, and migration using target-based, abundance-based and ssGSEA-based bioinformatic methods and in vitro validation. Following the construction of a protein-protein interaction network, 11 highly interconnected hub genes were identified and a five genes risk scoring model was developed to assess their potential prognostic ability. Our study will not only provide a basic miRNA-mRNA-phenotypes reference map for understanding the function of miR-654-5p in different cancers but also reveal the tumor-suppressing roles and prognostic values of miR-654-5p in lung cancer.

Graphical abstract

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category: cancer biology


title: CGRP-receptor family reveals endogenous GPCR agonist bias and its significance in primary human cardiovascular cells

abstract: Agonist bias at G protein-coupled receptors has attracted considerable interest, although its relevance for physiologically-produced agonists is not always clear. Here, using primary human cells and gene editing techniques, we demonstrate for the first time, endogenous agonist bias with physiological consequences for the calcitonin-like receptor (CLR). We reveal that by switching the accessory protein: receptor activity-modifying protein (RAMP) associated with CLR we can re-route the physiological pathways activated by the stimulating peptide agonists. These results have revealed a unique role in calcium-mediated nitric oxide signalling for the little-understood peptide adrenomedullin 2 and distinct pro-proliferative effects of calcitonin-gene related peptide (CGRP) and adrenomedullin in cardiovascular cells. This work reveals that CLR-based agonist bias occurs naturally in human cells and has a fundamental purpose for its existence. We anticipate this will be a starting point for more studies into RAMP function in native environments and its importance in endogenous GPCR signalling.

category: pharmacology and toxicology


title: ScoreNet: A Neural network-based post-processing model for identifying epileptic seizure onset and offset in EEGs

abstract: We design an algorithm to automatically detect epileptic seizure onsets and offsets from scalp EEGs. The proposed scheme consists of two sequential steps: detecting seizure episodes from long EEG recordings, and determining seizure onsets and offsets of the detected episodes. We introduce a neural network-based model called ScoreNet to carry out the second step by better predicting the seizure probability of pre-detected seizure epochs to determine seizure onsets and offsets. A cost function called log-dice loss with a similar meaning to the F1 score is proposed to handle the natural data imbalance inherent in EEG signals signifying seizure events. ScoreNet is then verified on the CHB-MIT Scalp EEG database in combination with several classifiers including random forest, CNN, and logistic regression. As a result, ScoreNet improves seizure detection performance over lone epoch-based seizure classification methods; F1 scores increase significantly from 16-37% to 53-70%, and false positive rates per hour decrease from 0.53-5.24 to 0.05-0.61. This method provides clinically acceptable latencies of detecting seizure onset and offset of less than 10 seconds. In addition, an effective latency index is proposed as a metric for detection latency whose scoring considers undetected events to provide better insight into onset and offset detection than conventional time-based metrics.

category: neuroscience


title: Analogous computations in working memory input, output and motor gating: Electrophysiological and computational modeling evidence

abstract:
Adaptive cognitive-control involves a hierarchical cortico-striatal gating system that supports selective updating, maintenance, and retrieval of useful cognitive and motor information. Here, we developed a task that independently manipulates selective gating operations into working-memory (input gating), from working-memory (output gating), and of responses (motor gating) and tested the neural dynamics and computational principles that support them. Increases in gating demands, captured by gate switches, were expressed by distinct EEG correlates at each gating level that evolved dynamically in partially overlapping time windows. Further, categorical representations of specific maintained items and of motor responses could be decoded from EEG when the corresponding gate was switching, thereby linking gating operations to prioritization. Finally, gate switching at all levels was related to increases in the motor decision threshold as quantified by the drift diffusion model. Together these results support the notion that cognitive gating operations scaffold on top of mechanisms involved in motor gating.

Author summaryHow do humans decide which information is relevant to attend to in memory, which cognitive operation to take, and when? Flexibly updating, maintenance and retrieval of relevant information from working memory (WM) are thought to be managed by gating computations in the frontostriatal network, supporting higher order learning and cognitive flexibility. Using the reference-back-2 task, we tested the key properties of gating. Namely that they are selective ("content-addressable") and that principles of cognitive "actions" (including input gating of WM, output gating from WM) are scaffold on top of the motor gating operations. Using trial-by-trial EEG indexing and quantitative computational modeling (the hierarchical drift-diffusion model) we showed that action selection at all three levels of gating have separable neural signatures but they operate partly in parallel, such that decisions about a response are processed to some degree even while the identity of the cognitive rule were uncertain. Furthermore, we showed analogous computations across levels of gating as selection of WM representation and of motor action lead to increase in the estimated decision threshold and to enhanced neural coding of the selected information thereby providing a novel link between WM gating and WM prioritization.


title: Probabilistic discrimination of relative stimulus features in mice

abstract: Understanding how the brain computes choice from sensory information is a central question in perceptual decision-making research. From a behavioral perspective, paradigms suitable to study perceptual decision-making condition choice on invariant properties of the stimuli, thus decoupling stimulus-specific information from decision-related variables. From a neural perspective, powerful tools for the dissection of brain circuits are needed, which suggests the mouse as a suitable animal model. However, whether and how mice can perform an invariant visual discrimination task has not yet been fully established. Here, we show that mice can solve a complex orientation discrimination task where the choices are decoupled from the orientation of individual stimuli. Moreover, we demonstrate a discrimination acuity of at least 6{degrees}, challenging the common belief that mice are poor visual discriminators. We reached these conclusions by introducing a novel probabilistic choice model that explained behavioral strategies in (n = 40) mice and identified unreported dimensions of variation associated with the circularity of the stimulus space. Furthermore, the model showed a dependence of history biases on task engagement, demonstrating behavioral sensitivity to the availability of cognitive resources. In conclusion, our results reveal that mice are capable of decoupling decision-relevant information from stimulus-specific information, thus demonstrating they are a useful animal model for studying neural representation of abstract learned categories in perceptual decision-making research.


title: Cross-covariance isolate detect: a new change-point method for estimating dynamic functional connectivity

abstract: Evidence of the non stationary behavior of functional connectivity (FC) networks has been observed in task based functional magnetic resonance imaging (fMRI) experiments and even prominently in resting state fMRI data. This has led to the development of several new statistical methods for estimating this time-varying connectivity, with the majority of the methods utilizing a sliding window approach. While computationally feasible, the sliding window approach has several limitations. In this paper, we circumvent the sliding window, by introducing a statistical method that finds change-points in FC networks where the number and location of change-points are unknown a priori. The new method, called cross-covariance isolate detect (CCID), detects multiple change-points in the second-order (cross-covariance or network) structure of multivariate, possibly high-dimensional time series. CCID allows for change-point detection in the presence of frequent changes of possibly small magnitudes, can assign change-points to one or multiple brain regions, and is computationally fast. In addition, CCID is particularly suited to task based data, where the subject alternates between task and rest, as it firstly attempts isolation of each of the change-points within subintervals, and secondly their detection therein. Furthermore, we also propose a new information criterion for CCID to identify the change-points. We apply CCID to several simulated data sets and to task based and resting state fMRI data and compare it to recent change-point methods. CCID may also be applicable to electroencephalography (EEG), magentoencephalography (MEG) and electrocorticography (ECoG) data. Similar to other biological networks, understanding the complex network organization and functional dynamics of the brain can lead to profound clinical implications. Finally, the R package ccid implementing the method from the paper is available from CRAN.


title: Coordinated Changes in Gene Expression Kinetics Underlie both Mouse and Human Erythroid Maturation

abstract:
BackgroundSingle cell technologies are transforming biomedical research, including the recent demonstration that unspliced pre-mRNA present in single cell RNA-Seq permits prediction of future expression states. Here we applied this  RNA velocity concept to an extended timecourse dataset covering mouse gastrulation and early organogenesis.

ResultsIntriguingly, RNA velocity correctly identified epiblast cells as the starting point, but several trajectory predictions at later stages were inconsistent with both real time ordering and existing knowledge. The most striking discrepancy concerned red blood cell maturation, with velocity-inferred trajectories opposing the true differentiation path. Investigating the underlying causes revealed a group of genes with a coordinated step-change in transcription, thus violating the assumptions behind current velocity analysis suites, which do not accommodate time-dependent changes in expression dynamics. Using scRNA-Seq analysis of chimeric mouse embryos lacking the major erythroid regulator Gata1, we show that genes with the step-changes in expression dynamics during erythroid differentiation fail to be up-regulated in the mutant cells, thus underscoring the coordination of modulating transcription rate along a differentiation trajectory. In addition to the expected block in erythroid maturation, the Gata1- chimera dataset revealed induction of PU.1 and expansion of megakaryocyte progenitors. Finally, we show that erythropoiesis in human fetal liver is similarly characterized by a coordinated step-change in gene expression.

ConclusionsBy identifying a limitation of the current velocity framework coupled with in vivo analysis of mutant cells, we reveal a coordinated step-change in gene expression kinetics during erythropoiesis, with likely implications for many other differentiation processes.

category: developmental biology


title: Noise Distorts the Epigenetic Landscape and Shapes Cell Fate Decisions

abstract: The Waddington epigenetic landscape has become an iconic representation of the cellular differentiation process. Recent single-cell transcriptomic data provide new opportunities for quantifying this originally conceptual tool, offering insight into the gene regulatory networks underlying cellular development. While many methods for constructing the landscape have been proposed, by far the most commonly employed approach is based on computing the landscape as the negative logarithm of the steady-state probability distribution. Here, we use simple models to highlight the complexities and limitations that arise when reconstructing the potential landscape in the presence of stochastic fluctuations. We consider how the landscape changes in accordance with different stochastic systems, and show that it is the subtle interplay between the deterministic and stochastic components of the system that ultimately shapes the landscape. We further discuss how the presence of noise has important implications for the identifiability of the regulatory dynamics from experimental data.


title: ISSRseq: an extensible method for reduced representation sequencing

abstract:
O_LIThe capability to generate densely sampled single nucleotide polymorphism (SNP) data is essential in diverse subdisciplines of biology, including crop breeding, pathology, forensics, forestry, ecology, evolution, and conservation. However, the wet-lab expertise and bioinformatics training required to conduct genome-scale variant discovery remain limiting factors for investigators with limited resources.
C_LIO_LIHere we present ISSRseq, a PCR-based method for reduced representation of genomic variation using simple sequence repeats as priming sites to sequence inter simple sequence repeat (ISSR) regions. Briefly, ISSR regions are amplified with single primers, pooled, used to construct sequencing libraries with a commercially-available kit, and sequenced on the Illumina platform. We also present a flexible bioinformatic pipeline that assembles ISSR loci, calls and hard filters variants, outputs data matrices in common formats, and conducts population analyses using R.
C_LIO_LIUsing three angiosperm species as case studies, we demonstrate that ISSRseq is highly repeatable, necessitates only simple wet-lab skills and commonplace instrumentation, is flexible in terms of the number of single primers used, and can generate genomic-scale variant discovery on par with existing RRS methods which require more complex wet lab procedures.
C_LIO_LIISSRseq represents a straightforward approach to SNP genotyping in any organism, and we predict that this method will be particularly useful for those studying population genomics and phylogeography of non-model organisms. Furthermore, the ease of ISSRseq relative to other RRS methods should prove useful to those lacking advanced expertise in wet lab methods or bioinformatics.
C_LI

category: genomics


title: HIV reverse transcriptase pre-steady-state kinetic analysis of chain terminators and translocation inhibitors reveals interactions between magnesium and nucleotide 3'-OH

abstract: Deoxythymidine triphosphate analogs with various 3' sugar groups (-OH (dTTP), -H, -N3, -NH2, -F, -O-CH3, no group (2',3'-didehydro-2',3'-dideoxythymidine triphosphate (d4TTP)), and those retaining the 3'-OH but with 4' additions (4'-C-methyl, 4'-C-ethyl) or sugar ring modifications (D-carba dTTP) were evaluated using pre-steady-state kinetics in low (0.5 mM) and high (6 mM) Mg2+ with HIV reverse transcriptase (RT). Analogs showed diminished incorporation rates (k) compared to dTTP ranging from about 2-fold (3'-H, -N3, and d4TTP with high Mg2+) to >10-fold (3'-NH2 and 3'-F with low Mg2+), while 3'-O-CH3 dTTP incorporated much slower than other analogs. Illustrating the importance of interactions between Mg2+ and the 3'-OH, k using 5 M dTTP and 0.5 mM Mg2+ was only modestly slower (1.6-fold) than with 6 mM Mg2+, while analogs with 3' alterations incorporated 2.8-5.1-fold slower in 0.5 mM Mg2+. In contrast, 4'-C-methyl and D-carb dTTP, which retain the 3'-OH, were not significantly affected by Mg2+. Consistent with these results, analogs with 3' modifications were better inhibitors in 6 mM vs. 0.5 mM Mg2+. Equilibrium dissociation constant (Kd) and kpol determinations for dTTP and analogs lacking a 3'-OH indicated that low Mg2+ caused a several-fold greater reduction in kpol with the analogs but had little effect on Kd, results consistent with a role for 3'-OH/Mg2+ interactions in catalysis rather than nucleotide binding. Overall, results emphasize the importance previously unreported interactions between Mg2+ and the 3'-OH of the incoming nucleotide and suggest inhibitors with 3'-OH groups may have advantages in the low free Mg2+ in physiological settings.

category: biochemistry


title: Combinatorial approach of binary colloidal crystals (BCCs) and CRISPR activation to improve induced pluripotent stem cell differentiation into neurons

abstract: Conventional methods of neuronal differentiation for human induced pluripotent stem cells (iPSCs) are tedious and complicated, involving multi-stage protocols with complex cocktails of growth factors and small molecules. Artificial extracellular matrix with defined surface topography and chemistry represents a promising venue to improve the neuronal differentiation in vitro. In the present study, we test the impact of a type of colloidal self-assembled patterns called binary colloidal crystals (BCCs) in neuronal differentiation. We developed a CRISPR activation (CRISPRa) iPSC platform that constitutively expresses the dCas9-VPR system, which allows robust activation of the proneural transcription factor NEUROD1 to rapidly induce neuronal differentiation within seven days. We showed that the combinatorial use of BCCs can further improve this neuronal differentiation system. In particular, our results indicate that fine tuning of silica and polystyrene size is critical to generate specific topographies to improve neuronal differentiation and branching. BCCs with 5 m silica and 100 nm carboxylated polystyrene has the most prominent effect on increasing neurite outgrowth and more complex ramification, while BCCs with 2m silica and 65nm carboxylated polystyrene is better in promoting neuronal enrichment. These results indicate that biophysical cues can support rapid differentiation and improve neuronal maturation. In summary, our combinatorial approach of CRISPRa and BCCs provides a robust and rapid pipeline for in vitro production of human neurons. Specific BCCs can be adapted to late stages of neuronal differentiation protocols to improve neuronal maturation, which have important implications in tissue engineering, in vitro biological studies and disease modeling.

category: bioengineering


title: Label2label: Training a neural network to selectively restore cellular structures in fluorescence microscopy

abstract: Fluorescence microscopy is an essential tool in cell biology to visualise the spatial distribution of proteins that dictates their role in cellular homeostasis, dynamic cellular processes, and dysfunction during disease. However, unspecific binding of the antibodies that are used to label a cellular target often leads to high background signals in the images, decreasing the contrast of a cellular structure of interest. Recently, convolutional neural networks (CNNs) have been successfully employed for denoising and upsampling in fluorescence microscopy, but current image restoration methods cannot correct for background signals originating from the label. Here, we report a new method to train a CNN as content filter for non-specific signals in fluorescence images that does not require a clean benchmark, using dual-labelling to generate the training data. We name this method label2label (L2L). In L2L, a CNN is trained with image pairs of two non-identical labels that target the same cellular structure of interest. We show that after L2L training a network restores images not only with reduced image noise but also label-induced unspecific fluorescence signal in images of a variety of cellular structures, resulting in images with enhanced structural contrast. By implementing a multi-scale structural similarity loss function, the performance of the CNN as a content filter is further enhanced, for example, in STED images of caveolae. We show evidence that, for this loss function, sample differences in the training data significantly decrease so-called hallucination effects in the restorations that we otherwise observe when training the CNN with images of the same label. We also assess the performance of a cycle generative adversarial network as a content filter after L2L training with unpaired image data. Lastly, we show that a CNN can be trained to separate structures in superposed fluorescence images of two different cellular targets, allowing multiplex imaging with microscopy setups where the number of excitation sources or detectors is limited.

category: bioinformatics


title: Cadherin-11 dimerization multi-site kinetics: combined partial unfolding and strand-swapping

abstract: Cadherin extracellular domain 1 (EC1) mediates homophilic dimerization in adherens junctions. Conserved Trp2 and Trp4 residues in type II cadherins anchor the EC1 A-strand intermolecularly in strand-swapped dimers. Herein, NMR spectroscopy is used to elucidate the roles of Trp2 and Trp4 in Cadherin-11 dimerization. The monomeric state, with the A-strand and Trp side chains packed intramolecularly, is in equilibrium with sparsely populated partially and fully A-strand-exposed states, in which Trp2 (and Trp4, respectively) side-chain packing is disrupted. Exchange kinetics between the major state and the partially (fully) A-strand-exposed state is slow-intermediate (intermediate-fast). A separate very fast process exchanges ordered and random-coil BC loop conformations with populations dependent on A-strand exposure and dimerization status. Additionally, very slow processes connect the folded A-strand-exposed conformation to partially unfolded states, which may represent additional domain-swapping intermediates. The dimerization mechanism of type II cadherins is revealed as coupled folding and strand-swapping.

category: biophysics


title: Design of novel CV-N variants: Modulation of binding dynamics through distal mutations

abstract: We develop a computational approach to identify distal residues that allosterically modulate dynamics of binding sites by combining dynamic coupling with statistical analysis of co-evolution. Putative mutants of the predicted allosteric sites are subjected to Adaptive BP-Dock for binding analysis. Here, we apply this method to a small lectin, Cyanovirin-N (CV-N), that selectively binds to dimannose. Our method points out mutations on I34, that is 16[A] away from binding pocket, can modulate binding. Experimental characterization confirms that I34K abolishes binding, while I34Y increases affinity. Increased affinity is not due to changes in the binding region, which are conserved in the crystal structure. However, ITC analysis reveals an opposite entropic contribution, suggesting that modulation of dynamics is responsible for the change in binding affinity. Our results point to a novel approach to identify and substitute distal sites by integrating evolutionary inference with protein dynamics in glycan-binding proteins to improve binding affinity.


title: To See, Not to See, or to See Poorly: Perceptual Quality and Guess Rate as a Function of Electroencephalography (EEG) Brain Activity in an Orientation Perception Task

abstract:
Detection of visual stimuli fluctuates over time, and these fluctuations have been shown to correlate with time-domain evoked activity and frequency-domain periodic activity. However, it is unclear if these fluctuations are related to a change in guess rate, perceptual quality, or both. Here we determined whether the quality of perception randomly varies across trials or is fixed so that the variability is the same. Then we estimated how perceptual quality and guess rate on an orientation perception task relates to EEG activity. Response errors were fitted to variable precision models and the standard mixture model to determine whether perceptual quality is from a varying or fixed distribution. Overall, the best fit was the standard mixture model that assumes response variability can be defined by a fixed distribution.

The power and phase of 2-7 Hz post-target activities were found to vary along with task performance in that more accurate trials had greater power, and the preferred phase differed significantly between accurate and guess trials. Guess rate and {sigma} were significantly lower on trials with high 2-3 Hz power than low and the difference started around 250 ms post-target.

These effects coincide with changes in the P3 ERP: there was a more positive deflection in the accurate trials vs guesses. These results suggest that the spread of errors (perceptual quality) can be characterized by a fixed range of values. Where the errors fall within that range is modulated by the post-target power in the lower frequency bands and their analogous ERPs.


title: Distinct molecular pathways govern presynaptic homeostatic plasticity

abstract: Presynaptic homeostatic plasticity (PHP) stabilizes synaptic transmission by counteracting impaired neurotransmitter receptor function through increased presynaptic release. PHP is thought to be triggered by impaired receptor function, and to involve a stereotypic signaling pathway. However, here we demonstrate that different receptor perturbations that similarly reduce synaptic activity result in vastly different responses at the Drosophila neuromuscular junction. While receptor inhibition by the glutamate receptor (GluR) antagonist {gamma}-DGG is not compensated by PHP, the GluR inhibitors PhTx-433 and Gyki induce compensatory PHP. Intriguingly, PHP triggered by PhTx and Gyki involve separable signaling pathways, including inhibition of distinct GluR subtypes, differential modulation of the active-zone scaffold Bruchpilot, and short-term plasticity. Moreover, while PHP upon Gyki treatment does not require genes promoting PhTx-induced PHP, it involves presynaptic Protein Kinase D. Thus, synapses not only respond differentially to similar activity impairments, but achieve homeostatic compensation via distinct mechanisms, highlighting the diversity of homeostatic signaling.


title: Differential role of type I and type II vestibular hair cells in two anti-gravity reflexes in the rat.

abstract: The tail-lift reflex and the air-righting reflex in rats are anti-gravity reflexes that depend on vestibular function. To begin identifying their cellular basis, this study examined the relationship between reflex loss and the graded lesions caused in the vestibular sensory epithelia by varying doses of an ototoxic compound. After ototoxic exposure, we recorded these reflexes using high speed video. The movies were used to obtain objective measures of the reflexes: the minimum angle formed by the nose, the back of the neck and the base of the tail during the tail-lift maneuver and the time to right in the air-righting test. The vestibular sensory epithelia were then collected from the rats and used to estimate the loss of type I (HCI), type II (HCII) and all hair cells (HC) in both central and peripheral parts of the crista, utricle, and saccule. As expected, tail-lift angles decreased, and air-righting times increased, while the numbers of HCs remaining in the epithelia decreased in a dose-dependent manner. The results demonstrated greater sensitivity of HCI compared to HCII to the IDPN ototoxicity, as well as a relative resiliency of the saccule compared to the crista and utricle. Comparing the functional measures with the cell counts, we observed that loss of the tail-lift reflex associates better with HCI than with HCII loss. In contrast, most HCI in the crista and utricle were lost before air-righting times increased. These data suggest that these reflexes depend on the function of non-identical populations of vestibular HCs.


title: Relationship between vestibular hair cell loss and deficits in two anti-gravity reflexes in the rat


title: Pastures and Climate Extremes: Impacts of cool season warming and drought on the productivity of key pasture species in a field experiment

abstract: Shifts in the timing, intensity and/or frequency of climate extremes, such as severe drought and heatwaves, can generate sustained shifts in ecosystem function with important ecological and economic impacts for rangelands and managed pastures. The Pastures and Climate Extremes experiment (PACE) in Southeast Australia was designed to investigate the impacts of a severe winter/spring drought (60% rainfall reduction) and, for a subset of species, a factorial combination of drought and elevated temperature (ambient +3 {degrees}C) on pasture productivity. The experiment included nine common pasture and Australian rangeland species from three plant functional groups (C3 grasses, C4 grasses and legumes) planted in monoculture. Winter/spring drought resulted in productivity declines of 45% on average and up to 74% for the most affected species (Digitaria eriantha) during the 6-month treatment period, with eight of the nine species exhibiting significant yield reductions. Despite considerable variation in species sensitivity to drought, C4 grasses were more strongly affected by this treatment than C3 grasses or legumes. Warming also had negative effects on cool-season productivity, associated at least partially with exceedance of optimum growth temperatures in spring and indirect effects on soil water content. The combination of winter/spring drought and year-round warming resulted in the greatest yield reductions. We identified responses that were either additive such that there was only as significant warming effect under drought (Festuca), or less-than-additive, where there was no drought effect under warming (Medicago), compared to ambient plots. Results from this study highlight the sensitivity of diverse pasture species to increases in winter and spring drought severity similar to those predicted for this region, and that anticipated benefits of cool-season warming are unlikely to be realised. Overall, the substantial negative impacts on productivity suggest that future, warmer, drier climates will result in shortfalls in cool-season forage availability, with profound implications for the livestock industry and natural grazer communities.

category: ecology


title: Ribosome profiling in Streptococcus pneumoniae reveals the role of methylation of 23S rRNA nucleotide G748 on ribosome stalling.

abstract:
2.(1) BackgroundMany nucleotides in 23S rRNA are methylated post-transcriptionally by methyltransferases and cluster around the peptidyltransferase center (PTC) and the nascent peptidyl exit tunnel (NPET) located in 50S subunit of 70S ribosome. Biochemical interactions between a nascent peptide and the tunnel may stall ribosome movement and affect expression levels of the protein. However, no studies have shown a role for NPET on ribosome stalling using an NPET mutant.

(2) ResultsA ribosome profiling assay in Streptococcus pneumoniae demonstrates for the first time that an NPET mutant exhibits completely different ribosome occupancy compared to wild-type. We demonstrate, using RNA footprinting, that changes in ribosome occupancy correlate with changes in ribosome stalling. Further, statistical analysis shows that short peptide sequences that cause ribosome stalling are species-specific and evolutionarily selected. NPET structure is required to realize these specie-specific ribosome stalling.

(3) ConclusionsResults support the role of NPET on ribosome stalling. NPET structure is required to realize the species-specific and evolutionary conserved ribosome stalling. These findings clarify the role of NPET structure on the translation process.


title: VirStrain: a strain identification tool for RNA viruses

abstract: 1Genome epidemiology, which uses genomic data to analyze the source and spread of infectious diseases, provides important information beyond interview-based methods. Given fast accumulation of sequenced viral genomes, a basic need in genome epidemiology is to identify which reference genomes are identical or closest to the ones in a sequenced sample. Then the associated metadata such as the geographical locations can be utilized to infer the transmission network. In this work, we deliver VirStrain, a fast and accurate tool for conducting strain-level analysis from short reads. By using a greedy covering algorithm, we are able to derive unique k-mer combinations for highly similar reference genomes. VirStrain is able to detect the most possible strain and also multiple strains that may simultaneously infect the same host. We tested VirStrain on three types of RNA viruses whose reference genomes have different similarity distri-butions. For each types of virus, we assessed VirStrain across multiple bench-mark datasets of different properties and complexity. The experimental results on both simulated and real sequencing data show that VirStrain outperforms other strain identification tools.


title: SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

abstract:
The identity and functions of specialized cell types are dependent on the complex interplay between signaling and transcriptional networks. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link cell-surface receptors to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to immune cell types in the blood to predict the coupling of signaling receptors with cell context-specific TFs. The predictions are validated by prior knowledge and flow cytometry analyses. SPaRTAN is then used to predict the signaling coupled TF states of tumor infiltrating CD8+ T cells in malignant peritoneal and pleural mesotheliomas. SPaRTAN greatly enhances the utility of CITE-seq datasets to uncover TF and cell-surface receptor relationships in diverse cellular states.

SignificanceRecently single-cell technologies such as CITE-seq have been developed that enable simultaneous quantitative analysis of cell-surface receptor expression with transcriptional states. To date, these datasets have not been used to systematically develop cell-context-specific maps of the interface between signaling and transcriptional regulators orchestrating cellular identity and function. We developed a computational framework, SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network) that integrates single-cell proteomic and transcriptomic data based on CITE-seq with cis-regulatory information. We applied our method to publicly available (PBMCs) and new CITE-seq datasets (mesothelioma). Our predicted TF activity and cell-surface receptor relationships are validated by prior knowledge as well as experimental testing. SPaRTAN reveals many previously unidentified surface-receptor associated TFs.


title: Self-Supervised Representation Learning of Protein Tertiary Structures (PtsRep) and Its Implications for Protein Engineering

abstract: In recent years, deep learning has been increasingly used to decipher the relationships among protein sequence, structure, and function. Thus far these applications of deep learning have been mostly based on primary sequence information, while the vast amount of tertiary structure information remains untapped. In this study, we devised a self-supervised representation learning framework (PtsRep) to extract the fundamental features of unlabeled protein tertiary structures deposited in the PDB, a total of 35,568 structures. The learned embeddings were challenged with two commonly recognized protein engineering tasks: the prediction of protein stability and prediction of the fluorescence brightness of green fluorescent protein (GFP) variants, with training datasets of 16,431 and 26,198 proteins or variants, respectively. On both tasks, PtsRep outperformed the two benchmark methods UniRep and TAPE-BERT, which were pre-trained on two much larger sets of data of 24 and 32 million protein sequences, respectively. Protein clustering analyses demonstrated that PtsRep can capture the structural signatures of proteins. Further testing of the GFP dataset revealed two important implications for protein engineering: (1) a reduced and experimentally manageable training dataset (20%, or 5,239 variants) yielded a satisfactory prediction performance for PtsRep, achieving a recall rate of 70% for the top 26 brightest variants with 795 variants in the testing dataset retrieved; (2) counter-intuitively, when only the bright variants were used for training, the performances of PtsRep and the benchmarks not only did not worsen but they actually slightly improved. This study provides a new avenue for learning and exploring general protein structural representations for protein engineering.


title: Cytopath: Simulation based inference of differentiation trajectories from RNA velocity fields

abstract:
AO_SCPLOWBSTRACTC_SCPLOWTrajectory inference from single-cell RNA sequencing data bears the potential to systematically reconstruct complex differentiation processes, however inferring trajectories that accurately model the biological characteristics of varied processes continues to be a challenge, notwithstanding the many available solutions. In general, trajectory and pseudotime inference methods have so far suffered from the ambiguity of static single-cell transcriptome snapshots lacking a concept of directionality and rate of transcriptional activity.

We report Cytopath, a method for trajectory inference that takes advantage of transcriptional activity information from RNA velocity of single-cells to perform trajectory inference. Cytopath performs this task by defining a Markov chain model, simulating an ensemble of possible differentiation trajectories and constructs a consensus trajectory. We show that Cytopath can recapitulate the topological and molecular characteristics of the differentiation process under study. In our analysis we include differentiation trajectories with varying bifurcated, circular, convergent and mixed topology studied in single-snapshot as well as time-series single-cell RNA sequencing experiments. We demonstrate superior and enabling capability to reconstruct differentiation trajectories in comparison to state-of-the art trajectory inference approaches.


title: An immunogenic model of KRAS-mutant lung cancer for study of targeted therapy and immunotherapy combinations

abstract: Mutations in oncogenes such as KRAS and EGFR cause a high proportion of lung cancers. Drugs targeting these proteins cause tumour regression but ultimately fail to cure these cancers, leading to intense interest in how best to combine them with other treatments, such as immunotherapies. However, preclinical systems for studying the interaction of lung tumours with the host immune system are inadequate, in part due to the low tumour mutational burden in genetically engineered mouse models. Here we set out to develop mouse models of mutant KRAS-driven lung cancer with an elevated tumour mutational burden by expressing the human DNA cytosine deaminase, APOBEC3B, to mimic the mutational signature seen in human lung cancer. This failed to substantially increase clonal tumour mutational burden and autochthonous tumours remained refractory to immunotherapy. However, by establishing clonal cell lines from these tumours we generated an immunogenic syngeneic transplantation model of KRAS mutant lung adenocarcinoma that was sensitive to immunotherapy. Unexpectedly, we found that anti-tumour immune responses were not directed against neoantigens but instead targeted derepressed endogenous retroviral antigens. The ability of KRASG12C inhibitors to cause regression of KRASG12C-expressing versions of these tumours was markedly potentiated by the adaptive immune system, providing a unique opportunity for the study of combinations of targeted and immunotherapies in immune-hot lung cancer.


title: Multiple overlapping dynamic patterns of the visual sensory network in schizophrenia

abstract: Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, that we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.


title: AF10 (MLLT10) prevents somatic cell reprogramming through regulation of H3K79 methylation

abstract: The histone H3 lysine 79 (H3K79) methyltransferase DOT1L is a key chromatin-based barrier to somatic cell reprogramming. However, the mechanisms by which DOT1L safeguards cell identity and somatic-specific transcriptional programs remain unknown. Here, we employed a proteomic approach using proximity-based labeling to identify DOT1L-interacting proteins and investigated their effects on reprogramming. Among DOT1L interactors, suppression of AF10 (MLLT10) via RNA interference or CRISPR/Cas9, significantly increases reprogramming efficiency. In somatic cells and induced pluripotent stem cells (iPSCs) higher order H3K79 methylation is dependent on AF10 expression. In AF10 knockout cells, re-expression wildtype AF10, but not a mutant defective in DOT1L binding, rescues overall H3K79 methylation and reduces reprogramming efficiency. Transcriptomic analyses during reprogramming show that AF10 suppression results in downregulation of fibroblast-specific genes and accelerates the activation of pluripotency-associated genes. Our findings establish AF10 as a novel barrier to reprogramming by regulating H3K79 methylation and thereby sheds light on the mechanism by which cell identity is maintained in somatic cells.


title: Dynamic Methylome Modification associated with mutational signatures in ageing and etiology of disease

abstract:
Reversible epigenetic changes within the loci of genes that regulate critical cell processes have recently emerged as important biomarkers of disease pathology. It is then natural to consider the consequences for population health risk of such epigenetic changes during the aging process. Specifically, the interplay between dynamic methylation changes that accompany aging and mutations that accrue in an individuals genome over time need further investigation. The current study investigated the role of dynamic methylation acting together with gene variants in an individual over time to gain insight into the evolving epigenome-genome interplay that affects biochemical pathways controlling physiological processes during aging.

We completed a whole-genome methylation and variant analysis in a non-smoking Zoroastrian-Parsi individual, collecting two samples, 12 years apart (at 53 and 65 years respectively) (ZPMetG-Hv2a-1A (old, t0), ZPMetG-Hv2a-1B (recent, t0+12)) and analysing them using a GridION Nanopore sequencer at 13X genome coverage overall. We further identified the single nucleotide variants (SNVs) and indels in known CpG islands by employing the Genome Analysis Tool Kit (GATK) and MuTect2 variant-caller pipeline with the GRCh37 (patch 13) human genome as reference.

We found 5258 disease-relevant genes that had been differentially methylated in this individual over 12 years. Employing the GATK pipeline, we found 24,948 genes, corresponding to 4,58,148 variants, specific to ZPMetG-Hv2a-1B, indicating the presence of variants that had accrued over time. A fraction of the gene variants (242/24948) occurred within the CpG regions that were differentially methylated, with 67/247 exactly coincident with a CpG site. Our analysis yielded a critical cluster of 10 genes that were each significantly methylated and had variants at the CpG site or the {+/-}4 bp CpG region window. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment network analysis as well as Reactome and STRING analysis of gene-specific variants indicated an impact on biological processes regulating the immune system, disease networks implicated in cancer and neurodegenerative diseases, and transcriptional control of processes regulating cellular senescence and longevity. Additional analysis of mutational signatures indicated a majority of C>T transitions followed by T>C transitions in the more recent sample, ZPMetG-Hv2a-1B.

Our current study provides additional insight into the aging methylome over time and the interplay between different methylation and gene variants in the etiology of disease.


title: Fast and memory-efficient mapping of short bisulfite sequencing reads using a two-letter alphabet

abstract: DNA cytosine methylation is an important epigenomic mark with a wide range of functions across many organisms. Whole genome bisulfite sequencing (WGBS) is the gold standard to interrogate cyto-sine methylation genome-wide. Algorithms used to map WGBS reads often encode the four-base DNA alphabet with three letters by reducing two bases to a common letter. This encoding substantially reduces the entropy of nucleotide frequencies in the resulting reference genome. Within the paradigm of read mapping by first filtering possible candidate alignments, reduced entropy of the reference can increase the required computing effort. We introduce another bisulfite mapping algorithm (abismal), based on the idea of encoding a four-letter DNA sequence as only two letters, one for purines and one for pyrimidines. We show that this encoding has greater specificity when subsequences are selected from reads for filtration. Through the two-letter encoding, the abismal software tool maps reads in less time and using less memory than most WGBS read mapping software tools, while attaining similar accuracy. This allows in silico methylation analysis to be performed in a wider range of computing machines with limited hardware settings.


title: LISA: Learned Indexes for Sequence Analysis

abstract:
BackgroundNext-generation sequencing (NGS) technologies have enabled affordable sequencing of billions of short DNA fragments at high throughput, paving the way for population-scale genomics. Genomics data analytics at this scale requires overcoming performance bottlenecks, such as searching for short DNA sequences over long reference sequences.

ResultsIn this paper, we introduce LISA (Learned Indexes for Sequence Analysis), a novel learning-based approach to DNA sequence search. We focus on accelerating two of the most essential flavors of DNA sequence search--exact search and super-maximal exact match (SMEM) search. LISA builds on and extends FM-index, which is the state-of-the-art technique widely deployed in genomics tools. Experiments with human, animal, and plant genome datasets indicate that LISA achieves up to 2.2 and 10.8 speedups over the state-of-the-art FM-index based implementations for exact search and super-maximal exact match (SMEM) search, respectively.

Code availabilityhttps://github.com/IntelLabs/Trans-Omics-Acceleration-Library/tree/master/LISA.


title: GNS561, a new autophagy inhibitor active against cancer stem cells in hepatocellular carcinoma and hepatic metastasis from colorectal cancer

abstract: Patients with advanced hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC) have a very poor prognosis due to the lack of efficient treatments. As observed in several other tumors, the effectiveness of treatments is mainly hampered by the presence of a highly tumorigenic sub-population of cancer cells called cancer stem cells (CSCs). Indeed, CSCs are resistant to chemotherapy and radiotherapy and have the ability to regenerate the tumor bulk. Hence, innovative drugs that are efficient against both bulk tumor cells and CSCs would likely improve cancer treatment. In this study, we demonstrated that GNS561, a new autophagy inhibitor that induces lysosomal cell death, showed significant activity against not only the whole tumor population but also a sub-population displaying CSC features (high ALDH activity and tumorsphere formation ability) in HCC and in liver mCRC cell lines. These results were confirmed in vivo in HCC from a DEN-induced cirrhotic rat model in which GNS561 decreased tumor growth and reduced the frequency of CSCs (CD90+CD45-). Accordingly, GNS561, which was in a global phase 1b clinical trial in liver cancers that was recently successful, offers great promise for cancer therapy by exterminating both the tumor bulk and the CSC sub-population.


title: Is the brain macroscopically linear? A system identification of resting state dynamics

abstract: A central challenge in the computational modeling of neural dynamics is the trade-off between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are both experimentally established and essential for neuronal functioning. One may therefore expect the collective dynamics of massive networks of such neurons to exhibit an even larger repertoire of nonlinear behaviors. An implicit assumption has thus formed that an "accurate" computational model of whole-brain dynamics must inevitably be non-linear whereas linear models may provide a first-order approximation. To what extent this assumption holds, however, has remained an open question. Here, we provide new evidence that challenges this assumption at the level of whole-brain blood-oxygen-level-dependent (BOLD) and macroscopic field potential dynamics by leveraging the theory of system identification. Using functional magnetic resonance imaging (fMRI) and intracranial electroencephalography (iEEG), we model the spontaneous, resting state activity of 700 subjects in the Human Connectome Project (HCP) and 122 subjects from the Restoring Active Memory (RAM) project using state-of-the-art linear and nonlinear model families. We assess relative model fit using predictive power, computational complexity, and the extent of residual dynamics unexplained by the model. Contrary to our expectations, linear auto-regressive models achieve the best measures across all three metrics. To understand and explain this linearity, we highlight four properties of macroscopic neurodynamics which can counteract or mask microscopic nonlinear dynamics: averaging over space, averaging over time, observation noise, and limited data samples. Whereas the latter two are technological limitations and can improve in the future, the former two are inherent to aggregated macroscopic brain activity. Our results demonstrate the discounted potential of linear models in accurately capturing macroscopic brain dynamics. This, together with the unparalleled interpretability of linear models, can greatly facilitate our understanding of macroscopic neural dynamics, which in turn may facilitate the principled design of model-based interventions for the treatment of neuropsychiatric disorders.


title: Visual recognition is heralded by shifts in local field potential oscillations and inhibitory networks in primary visual cortex

abstract:
Learning to recognize and filter familiar, irrelevant sensory stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process, and oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. We show here that LFP oscillatory activity in visual cortex is profoundly altered as male and female mice learn to recognize an oriented grating stimulus--low frequency ([~]15 Hz peak) power sharply increases while high frequency ([~]65 Hz peak) power decreases. These changes report recognition of the familiar pattern, as they disappear when the stimulus is rotated to a novel orientation. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns. We propose a model in which the balance of two interacting interneuron circuits shifts as novel stimuli become familiar.

Significance StatementHabituation, familiarity and novelty detection are fundamental cognitive processes that enable organisms to adaptively filter meaningless stimuli and focus attention on potentially important elements of their environment. We have shown that this process can be studied fruitfully in the mouse primary visual cortex by using simple grating stimuli for which novelty and familiarity are defined by orientation, and by measuring stimulus-evoked and continuous local field potentials. Altered event-related and spontaneous potentials, and deficient habituation, are well-documented features of several neurodevelopmental psychiatric disorders. The paradigm described here will be valuable to interrogate the origins of these signals and the meaning of their disruption more deeply.


title: Paradoxical neuronal hyperexcitability in a mouse model of mitochondrial pyruvate import deficiency

abstract:
Neuronal excitation imposes a high demand of ATP in neurons. Most of the ATP derives primarily from pyruvate-mediated oxidative phosphorylation, a process that relies on import of pyruvate into mitochondria occuring exclusively via the mitochondrial pyruvate carrier (MPC). To investigate whether deficient oxidative phosphorylation impacts neuron excitability, we generated a mouse strain carrying a conditional deletion of MPC1, an essential subunit of the mitochondrial pyruvate carrier, specifically in adult glutamatergic neurons. We found that, despite decreased levels of oxidative phosphorylation in these excitatory neurons, mice were normal at rest. Paradoxically, in response to mild inhibition of GABA mediated synaptic activity, they rapidly developed severe seizures and died, whereas under similar conditions the behaviour of control mice remained unchanged. We show that neurons with a deficient MPC are intrinsically hyperexcitable as a consequence of impaired calcium homeostasis, which reduces M-type potassium channel activity. Provision of ketone bodies restores energy status, calcium homeostasis and M-channel activity and attenuates seizures in animals fed a ketogenic diet. Our results provide an explanation for the paradoxical seizures that frequently accompany a large number of neuropathologies, including cerebral ischemia and diverse mitochondriopathies, in which neurons experience an energy deficit.

One Sentence SummaryDecreased OXPHOS and Ca2+-mediated neuronal hyperexcitability lead to seizure in a mouse model of mitochondrial pyruvate import deficiency.


title: Identification of SUMO targets required to maintain human stem cells in the pluripotent state.

abstract: To determine the role of SUMO modification in the maintenance of pluripotent stem cells we used ML792, a potent and selective inhibitor of SUMO Activating Enzyme. Treatment of human induced pluripotent stem cells with ML792 initiated changes associated with loss of pluripotency such as reduced expression of key pluripotency markers. To identify putative effector proteins and establish sites of SUMO modification, cells were engineered to stably express either SUMO1 or SUMO2 with TGG to KGG mutations that facilitate GlyGly-K peptide immunoprecipitation and identification. A total of 976 SUMO sites were identified in 427 proteins. STRING enrichment created 3 networks of proteins with functions in regulation of gene expression, ribosome biogenesis and RNA splicing, although the latter two categories represented only 5% of the total GGK peptide intensity. The remainder have roles in transcription and chromatin structure regulation. Many of the most heavily SUMOylated proteins form a network of zinc-finger transcription factors centred on TRIM28 and associated with silencing of retroviral elements. At the level of whole proteins there was only limited evidence for SUMO paralogue-specific modification, although at the site level there appears to be a preference for SUMO2 modification over SUMO1 in acidic domains. We show that SUMO is involved in the maintenance of the pluripotent state in hiPSCs and identify many chromatin-associated proteins as bona fide SUMO substrates in human induced pluripotent stem cells.

category: cell biology


title: Deep manifold learning reveals hidden dynamics of proteasome autoregulation

abstract: The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation.


title: Hidden dynamics of human proteasome autoregulation during protein degradation


title: Hidden dynamics of proteasome autoregulation discovered by cryo-EM data-driven deep learning


title: Cell cycle corruption in a preleukemic ETV6-RUNX1 model exposes RUNX1 addiction as a therapeutic target in acute lymphoblastic leukemia

abstract: The ETV6-RUNX1 onco-fusion arises in utero, initiating a clinically silent pre-leukemic state associated with the development of pediatric B-acute lymphoblastic leukemia (B-ALL). We characterize the ETV6-RUNX1 regulome by integrating chromatin immunoprecipitation- and RNA-sequencing and show that ETV6-RUNX1 functions primarily through competition for RUNX1 binding sites and transcriptional repression. In pre-leukemia, this results in ETV6-RUNX1 antagonization of cell cycle regulation by RUNX1 as evidenced by mass cytometry analysis of B-lineage cells derived from ETV6-RUNX1 knock-in human pluripotent stem cells. In frank leukemia, knockdown of RUNX1 or its co-factor CBF{beta} results in cell death suggesting sustained requirement for RUNX1 activity which is recapitulated by chemical perturbation using an allosteric CBF{beta}-inhibitor. Strikingly, we show that RUNX1 addiction extends to other genetic subtypes of pediatric B-ALL and also adult disease. Importantly, inhibition of RUNX1 activity spares normal hematopoiesis. Our results implicate chemical intervention in the RUNX1 program as an exciting therapeutic opportunity in ALL.


title: Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation

abstract: Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing1-3. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary4,5. Chemical labeling-based single-cell approaches introduce hundreds of cells into the MS, but direct analysis of single cells has not yet reached the necessary sensitivity, robustness and quantitative accuracy to answer biological questions6,7. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography and a novel trapped ion mobility mass spectrometer, resulting in a more than ten-fold improved sensitivity. We accurately and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators such as CDK2NA, the E2 ubiquitin ligase UBE2S, DNA topoisomerases TOP2A/B and the chromatin regulator HMGA1. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable core proteome despite perturbation, while the transcriptome appears volatile. This emphasizes substantial regulation of translation and sets the stage for its elucidation at the single cell level. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material8, posttranslational modifications and small molecule studies to gain unprecedented insights into cellular heterogeneity in health and disease.

category: systems biology


title: GABA relates to functional connectivity changes and retention in visuomotor adaptation

abstract: Motor adaptation is fundamental to maintaining accurate movements under changing conditions, but the neurochemical basis of human motor adaptation is not well understood. Here, we used an ultra-high-field MR multimodal acquisition to address the hypothesis that M1 GABA and M1-Cerebellar functional connectivity would relate to retention of adaptation, but not acquisition of adaptation. As such, we demonstrate higher baseline M1 [GABA] relates to greater retention but does not relate to adaptation-acquisition. This relationship is mediated by change in M1-Cerebellar functional connectivity: higher M1 [GABA] relates to a decreased M1-Cerebellar connectivity, resulting in greater retention. These findings showed anatomical, neurochemical and behavioural specificity: As expected, no relationship was found between retention and a control metabolite, retention and connectivity change between control regions and between M1 [GABA] and behaviour in a control condition. The implication of a mechanistic link from neurochemistry to retention advances our understanding of population variability in retention and provides a step towards therapeutic interventions to restore motor abilities.


title: Identification of molecular candidates which regulate calcium-dependent CD8+ T-cell cytotoxicity

abstract: Cytotoxic CD8+ T lymphocytes (CTL) eliminate infected cells or transformed tumour cells by releasing perforin-containing cytotoxic granules at the immunological synapse. The secretion of such granules depends on Ca2+-influx through store operated Ca2+ channels, formed by STIM-activated Orai proteins. Whereas molecular mechanisms of the secretion machinery are well understood, much less is known about the molecular machinery that regulates the efficiency of Ca2+-dependent target cell killing. Here, we isolated total RNA from natural killer (NK) cells, non-stimulated CD8+ T-cells, and from Staphylococcus aureus enterotoxin A (SEA) stimulated CD8+ T-cells (SEA-CTL) and conducted whole genome expression profiling by microarray experiments. Based on differential expression analysis of the transcriptome data and analysis of master regulator genes, we identified 31 candidates which potentially regulate Ca2+-homeostasis in CTL. To investigate a putative function of these candidates in CTL cytotoxicity, we transfected either SEA-stimulated CTL (SEA-CTL) or antigen specific CD8+ T-cell clones (CTL-MART-1) with siRNAs specific against the identified candidates and analyzed the killing capacity using a real-time killing assay. In addition, we complemented the analysis by studying the effect of inhibitory substances acting on the candidate proteins if available. Finally, to unmask their involvement in Ca2+ dependent cytotoxicity, candidates were also analyzed under Ca2+-limiting conditions. Overall, this strategy led to the identification of KCNN4, RCAN3, CCR5 and BCL2 as potential candidates to regulate the efficiency of Ca2+-dependent target cell killing.

category: immunology


title: Phylogenetic and population structure analyses uncover pervasive misclassification and help assessing the biosafety of Pseudomonas putida for biotechnological applications

abstract: The Pseudomonas putida group comprises strains with biotechnological and clinical relevance. P. alloputida was proposed as a new species and highlighted the misclassification of P. putida. Nevertheless, the population structure of P. alloputida remained unexplored. We retrieved 11,025 Pseudomonas genomes and used P. alloputida Kh7T to delineate the species. The P. alloputida population structure comprises at least 7 clonal complexes (CCs). Clinical isolates are mainly found in CC4 and acquired resistance genes are present at low frequency in plasmids. Virulence profiles support the potential of CC7 members to outcompete other plant or human pathogens through a type VI secretion system. Finally, we found that horizontal gene transfer had an important role in shaping the ability of P. alloputida to bioremediate aromatic compounds such as toluene. Our results provide the grounds to understand P. alloputida genetic diversity and safety for environmental applications.

category: microbiology


title: Phylogenetic and population structure analyses uncover pervasive misclassification and help assessing the biosafety of Pseudomonas alloputida for biotechnological applications


title: The anatomy of a phenological mismatch: interacting consumer demand and resource characteristics determine the consequences of mismatching

abstract: Climate change has caused shifts in seasonally recurring biological events and the temporal decoupling of consumer-resource pairs - i.e., phenological mismatching (hereafter,  mismatching). Despite the hypothetical risk mismatching poses to consumers, it does not invariably lead to individual- or population-level effects. This may stem from how mismatches are typically defined, where an individual or population are  matched or mismatched based on the degree of asynchrony with a resource pulse. However, because both resource availability and consumer demands change over time, this categorical definition can obscure within- or among-individual fitness effects. We investigated the effects of resource characteristics on the growth, daily survival, and fledging rates of Hudsonian godwit (Limosa haemastica) chicks hatched near Beluga River, Alaska. To do this, we developed models to identify the effects of resource characteristics on individual- and population-level processes and determine how the strength of these effects change throughout a consumers early development. We found that at the individual-level, chick growth and survival improved following periods of higher invertebrate abundance but were increasingly dependent on the availability of larger prey as chicks aged. At the population level, seasonal fledging rates were best explained by a model including age-structured consumer demand. Our study suggests that modelling the effects of mismatching as a disrupted interaction between consumers and their resources provides a biological mechanism for how mismatching occurs and clarifies when it matters to individuals and populations. Given the variable responses to mismatching exhibited by consumer populations, such tools for predicting how populations may respond under future climatic conditions will be critical for conservation planning.


title: Interplay between extreme drift and selectionintensities favors the fixation of beneficial mutations in selfing maize populations

abstract: Population and quantitative genetic models provide useful approximations to predict long-term selection responses sustaining phenotypic shifts, and underlying multilocus adaptive dynamics. Valid across a broad range of parameters, their use for understanding the adaptive dynamics of small selfing populations undergoing strong selection intensity (thereafter High Drift-High selection regime, HDHS) remains to be explored. Saclay Divergent Selection Experiments (DSEs) on maize flowering time provide an interesting example of populations evolving under HDHS, with significant selection responses over 20 generations in two directions. We combined experimental data from Saclay DSEs, forward individual-based simulations, and theoretical predictions to dissect the evolutionary mechanisms at play in the observed selection responses. We asked two main questions: How do mutations arise, spread, and reach fixation in populations evolving under HDHS ? How does the interplay between drift and selection influence observed phenotypic shifts ? We showed that the long-lasting response to selection in small populations is due to the rapid fixation of mutations occurring during the generations of selection. Among fixed mutations, we also found a clear signal of enrichment for beneficial mutations revealing a limited cost of selection. Both environmental stochasticity and variation in selection coefficients likely contributed to exacerbate mutational effects, thereby facilitating selection grasp and fixation of small-effect mutations. Together our results highlight that despite a small number of polymorphic loci expected under HDHS, adaptive variation is continuously fueled by a vast mutational target. We discuss our results in the context of breeding and long-term survival of small selfing populations.

category: evolutionary biology


title: Virtue as the mean: Pan-human consensus genome significantly improves the accuracy of RNA-seq analyses

abstract: The Human Reference Genome serves as the foundation for modern genomic analyses. However, in its present form, it does not adequately represent the vast genetic diversity of the human population. In this study, we explored the consensus genome as a potential successor of the current Reference genome and assessed its effect on the accuracy of RNA-seq read alignment. In order to find the best haploid genome representation, we constructed consensus genomes at the Pan-human, Super-population and Population levels, utilizing variant information from the 1000 Genomes project. Using personal haploid genomes as the ground truth, we compared mapping errors for real RNA-seq reads aligned to the consensus genomes versus the Reference genome. For reads overlapping homozygous variants, we found that the mapping error decreased by a factor of ~2-3 when the Reference was replaced with the Pan-human consensus genome. Interestingly, we also found that using more population-specific consensuses resulted in little to no increase over using the Pan-human consensus, suggesting a limit in the utility of incorporating more specific genomic variation. To assess the functional impact, we compared splice junction expression in the different genomes and found that the Pan-human consensus increases accuracy of splice junction quantification for hundreds of splice junctions.


title: Identifying and testing marker-trait associations for growth and phenology in three pine species

abstract: In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.

category: plant biology


title: Identifying and testing marker-trait associations for growth and phenology in three pine species: implications for genomic prediction


title: Female meiosis II and pronuclear fusion require Bicaudal-D

abstract: Drosophila Clathrin heavy chain (Chc) is transported by the dynein/dynactin microtubule motor through its interaction with the adaptor protein Bicaudal-D (BicD). Here we show that Drosophila BicD and Chc localize to centrosomes and spindles during mitosis and to the tandem spindles during female meiosis II. Reducing the activity of BicD::GFP specifically in freshly laid eggs revealed that BicD is essential for the production of normal female meiosis II products and for pronuclear fusion. Chc interacts with BicD and D-TACC, and BicD is needed to correctly localize the microtubule-stabilizing factors D-TACC, clathrin, and Msps to the meiosis II spindles, suggesting that BicD acts by localizing these proteins. In unfertilized eggs, reduced BicD levels cause the female meiotic products to re-enter the cell cycle. As BicD is required to localize the spindle assembly checkpoint (SAC) components Mad2 and BubR1 to the female meiotic products, it appears that BicD functions to localize them to control metaphase arrest of polar bodies. Finally, Drosophila and C. elegans orthologs of BicD and tacc are also needed for pronuclear fusion.


title: The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

abstract: The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.


title: The evolutionary assembly of forest communities along environmental gradients: recent diversification or sorting of pre-adapted clades?

abstract:
O_LIBiogeographic events occurring in the deep past can contribute to the structure of modern ecological communities. However, little is known about how the emergence of environmental gradients shape the evolution of species that underlie community assembly. In this study, we address how the creation of novel environments lead to community assembly via two non-mutually exclusive processes: 1) the immigration and ecological sorting of pre-adapted clades (ISPC), and 2) recent adaptive diversification (RAD). We study these processes in the context of the elevational gradient created by the uplift of the Central Andes.
C_LIO_LIWe develop a novel approach and method based on the decomposition of species turnover into within- and among-clade components, where clades correspond to lineages that originated before mountain uplift. Effects of ISPC and RAD can be inferred from how components of turnover change with elevation. We test our approach using data from over 500 Andean forest plots.
C_LIO_LIWe found that species turnover between communities at different elevations is dominated by the replacement of clades that originated before the uplift of the Central Andes.
C_LIO_LIOur results suggest that immigration and sorting of clades pre-adapted to montane habitats is the primary mechanism shaping communities across elevations.
C_LI


title: Evolutionary tracking of SARS-CoV-2 genetic variants highlights intricate balance of stabilizing and destabilizing mutations

abstract:
The currently ongoing COVID-19 pandemic caused by SARS-CoV-2 has accounted for millions of infections and deaths across the globe. Genome sequences of SARS-CoV-2 are being published daily in public databases and the availability of this genome datasets has allowed unprecedented access into the mutational patterns of SARS-CoV-2 evolution. We made use of the same genomic information for conducting phylogenetic analysis and identifying lineage-specific mutations. The catalogued lineage defining mutations were analysed for their stabilizing or destabilizing impact on viral proteins. We recorded persistence of D614G, S477N, A222V V1176F variants and a global expansion of the PANGOLIN variant B.1. In addition, a retention of Q57H (B.1.X), R203K/G204R (B.1.1.X), T85I (B.1.2-B.1.3), G15S+T428I (C.X) and I120F (D.X) variations was observed. Overall, we recorded a striking balance between stabilizing and destabilizing mutations, therefore well-maintained protein structures. With selection pressures in the form of newly developed vaccines and therapeutics to mount soon in coming months, the task of mapping of viral mutations and recording of their impact on key viral proteins would be crucial to pre-emptively catch any escape mechanism that SARS-CoV-2 may evolve for.

STUDY IMPORTANCEAs large numbers of the SARS CoV-2 genome sequences are shared in publicly accessible repositories, it enables scientists a detailed evolutionary analysis since its initial isolation in Wuhan, China. We investigated the evolutionarily associated mutational diversity overlaid on the major phylogenetic lineages circulating globally, using 513 representative genomes. We detailed phylogenetic persistence of key variants facilitating global expansion of the PANGOLIN variant B.1, including the recent, fast expanding, B.1.1.7 lineage. The stabilizing or destabilizing impact of the catalogued lineage defining mutations on viral proteins indicates their possible involvement in balancing the protein function and structure. A clear understanding of this mutational profile is of high clinical significance to catch any vaccine escape mechanism, as the same proteins make crucial components of vaccines recently approved and in development. In this direction, our study provides an imperative framework and baseline data upon which further analysis could be built as newer variants of SARS-CoV-2 continue to appear.


title: SARS-CoV-2 Genomic Surveillance in Costa Rica: Evidence of a Divergent Population and an Increased Detection of a Spike T1117I Mutation

abstract:
Genome sequencing is a key strategy in the surveillance of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Latin America is the hardest hit region of the world, accumulating almost 20% of COVID-19 cases worldwide. Costa Rica was first exemplary for the region in its pandemic control, declaring a swift state of emergency on March 16th that led to a low quantity of cases, until measures were lifted in early May. From the first detected case in March 6th to December 31st almost 170 000 cases have been reported in Costa Rica, 99.5% of them from May onwards. We analyzed the genomic variability during the SARS-CoV-2 pandemic in Costa Rica using 185 sequences, 52 from the first months of the pandemic, and 133 from the current wave.

Three GISAID clades (G, GH, and GR) and three PANGOLIN lineages (B.1, B.1.1, and B.1.291) are predominant, with phylogenetic relationships that are in line with the results of other Latin American countries, suggesting introduction and multiple re-introductions from other regions of the world. The whole-genome variant calling analysis identified a total of 283 distinct nucleotide variants. These correspond mostly to non-synonymous mutations (51.6%, 146) but 45.6% (129) corresponded to synonymous mutations. The 283 variants showed an expected power-law distribution: 190 single nucleotide mutations were identified in single sequences, only 16 single nucleotide mutations were found in >5% sequences, and only two mutations in >50% genomes. These mutations were distributed through the whole genome. However, 63.6% were present in ORF1ab, 11.7% in Spike gene and 10.6% in the Nucleocapsid gene. Additionally, the prevalence of worldwide-found variant D614G in the Spike (98.9% in Costa Rica), ORF8 L84S (1.1%) is similar to what is found elsewhere. Interestingly, the frequency of mutation T1117I in the Spike has increased during the current pandemic wave beginning in May 2020 in Costa Rica, reaching 29.2% detection in the full genome analyses in November 2020. This variant has been observed in less than 1% of the GISAID reported sequences worldwide in all the 2020. Structural modeling of the Spike protein with the T1117I mutation suggest a potential effect on the viral oligomerization needed for cell infection, but no differences with other genomes on transmissibility, severity nor vaccine effectiveness are predicted. Nevertheless, in-vitro experiments are required to support these in-silico findings. In conclusion, genome analyses of the SARS-CoV-2 sequences over the course of COVID-19 pandemic in Costa Rica suggest introduction of lineages from other countries as travel bans and measures were lifted, similar to results found in other studies, as well as an increase in the Spike-T1117I variant that needs to be monitored and studied in further analyses as part of the surveillance program during the pandemic.


title: 15-PGDH Regulates Hematopoietic and Gastrointestinal Fitness During Aging

abstract:
Emerging evidence implicates the eicosanoid molecule prostaglandin E2 (PGE2) in conferring a regenerative phenotype to multiple organ systems following tissue injury. As aging is in part characterized by loss of tissue stem cells regenerative capacity, we tested the hypothesis that the prostaglandin-degrading enzyme 15-hydroxyprostaglandin dehydrogenase (15-PGDH) contributes to the diminished organ fitness of aged mice. Here we demonstrate that genetic loss of 15-PGDH (Hpgd) confers a protective effect on aging of murine hematopoietic and gastrointestinal (GI) tissues. Aged mice lacking 15-PGDH display increased hematopoietic output as assessed by peripheral blood cell counts, bone marrow and splenic stem cell compartments, and accelerated post-transplantation recovery compared to their WT counterparts. Loss of Hpgd expression also resulted in enhanced GI fitness and reduced local inflammation in response to colitis. Together these results suggest that 15-PGDH negatively regulates aged tissue regeneration, and that 15-PGDH inhibition may be a viable therapeutic strategy to ameliorate age-associated loss of organ fitness.

ARTICLE SUMMARY15-PGDH as a Driver of Age-Related Tissue Dysfunction

category: pathology


title: Diffusion Fails to Make a Stink

abstract: In this work we consider the question of whether a simple diffusive model can explain the scent tracking behaviors found in nature. For such tracking to occur, both the concentration of a scent and its gradient must be above some threshold. Applying these conditions to the solutions of various diffusion equations, we find that a purely diffusive model cannot simultaneously satisfy the tracking conditions when parameters are in the experimentally observed range. This demonstrates the necessity of modelling odor dispersal with full fluid dynamics, where non-linear phenomena such as turbulence play a critical role.


title: The assisting role of Polη in transcription facilitates formation of damage-induced cohesion

abstract:
The structural maintenance of chromosome (SMC) complex cohesin mediates sister chromatid cohesion established during replication, and damage-induced cohesion formed in response to DSBs post-replication. The translesion synthesis polymerase Pol{eta} is required for damage-induced cohesion through a hitherto unknown mechanism. Since Pol{eta} is functionally associated with transcription, and transcription triggers de novo cohesion in Schizosaccharomyces pombe, we hypothesized that transcription facilitates damage-induced cohesion in Saccharomyces cerevisiae. Here, we show dysregulated transcriptional profiles in Pol{eta}-depleted cells (rad30{Delta}), where genes involved in chromatin assembly and positive transcription regulation were downregulated. In addition, chromatin association of RNA polymerase II was reduced at promoters and coding regions in rad30{Delta} compared to WT cells, while occupancy of the H2A.Z variant (Htz1) at promoters was increased in rad30{Delta} cells. Perturbing histone exchange at promoters inactivated damage-induced cohesion, similarly to deletion of the RAD30 gene. Conversely, altering regulation of transcription elongation suppressed the deficient damage-induced cohesion in rad30{Delta} cells. These results indicate that Pol{eta} has an assisting role during the transcriptional process, which consecutively facilitates formation of damage-induced cohesion. This further suggests a potential linkage between regulation of transcription and formation of damage-induced cohesion after replication.

Author SummaryThe cohesin complex dynamically associates with chromosomes and holds sister chromatids together through cohesion established during replication. This ensures faithful chromosome segregation at anaphase. In budding yeast, DNA double strand breaks trigger sister chromatid cohesion even after replication. This so-called damage-induced cohesion is formed both close to the breaks, and genome-wide on undamaged chromosomes. The translesion synthesis polymerase eta (Pol{eta}) is specifically required for genome wide damage-induced cohesion. Although Pol{eta} is well characterized for its function in bypassing ultraviolet-induced DNA lesions, its mechanistic role in damage-induced cohesion is unclear. Here, we show that transcriptional regulation is perturbed in the absence of Pol{eta}. We propose that Pol{eta} could aid in chromatin association of RNA polymerase II through phosphorylation of the Pol{eta}-S14 residue, a non-canonical role of Pol{eta} which further facilitates formation of damage-induced cohesion genome wide. In addition, we observe the need of replication-independent nucleosome assembly/histone exchange for formation of damage-induced cohesion. This together provides new insight into formation of damage-induced cohesion after replication, which will be interesting to further explore.


title: Rare coding variants in 35 genes associate with circulating lipid levels: a multi-ancestry analysis of 170,000 exomes

abstract: Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency<1%) predicted damaging coding variation using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels. Ten of these: ALB, SRSF2, JAK2, CREB3L3, TMEM136, VARS, NR1H3, PLA2G12A, PPARG and STAB1 have not been implicated for lipid levels using rare coding variation in population-based samples. We prioritize 32 genes identified in array-based genome-wide association study (GWAS) loci based on gene-based associations, of which three: EVI5, SH2B3, and PLIN1, had no prior evidence of rare coding variant associations. Most of the associated genes showed evidence of association in multiple ancestries. Also, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes, and for genes closest to GWAS index single nucleotide polymorphisms (SNP). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

category: genetics


title: Cytosolic localization and in vitro assembly of human de novo thymidylate synthesis complex

abstract: De novo thymidylate synthesis is a crucial pathway for normal and cancer cells. Deoxythymidine monophosphate (dTMP) is synthesized by the combined action of three enzymes: serine hydroxymethyltransferase (SHMT), dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), the latter two targets of widely used chemotherapeutics such as antifolates and 5-fluorouracil. These proteins translocate to the nucleus after SUMOylation and are suggested to assemble in this compartment into the thymidylate synthesis complex (dTMP-SC). We report the intracellular dynamics of the complex in lung cancer cells by in situ proximity ligation assay, showing that it is also detected in the cytoplasm. This result strongly indicates that the role of the dTMP-SC assembly may go beyond dTMP synthesis. We have successfully assembled the dTMP synthesis complex in vitro, employing tetrameric SHMT1 and a bifunctional chimeric enzyme comprising human TYMS and DHFR. We show that the SHMT1 tetrameric state is required for efficient complex assembly, indicating that this aggregation state is evolutionary selected in eukaryotes to optimize protein-protein interactions. Lastly, our results on the activity of the complete thymidylate cycle in vitro, may provide a useful tool to develop drugs targeting the entire complex instead of the individual components.


title: RoDiCE: Robust differential protein co-expression analysis for cancer complexome

abstract:
MotivationThe full spectrum of abnormalities in cancer-associated protein complexes remains largely unknown. Comparing the co-expression structure of each protein complex between tumor and healthy cells may provide insights regarding cancer-specific protein dysfunction. However, the technical limitations of mass spectrometry-based proteomics, including contamination with biological protein variants, causes noise that leads to non-negligible over- (or under-) estimating co-expression.

ResultsWe propose a robust algorithm for identifying protein complex aberrations in cancer based on differential protein co-expression testing. Our method based on a copula is sufficient for improving identification accuracy with noisy data compared to conventional linear correlation-based approaches. As an application, we use large-scale proteomic data from renal cancer to show that important protein complexes, regulatory signaling pathways, and drug targets can be identified. The proposed approach surpasses traditional linear correlations to provide insights into higher order differential co-expression structures.

Availability and Implementationhttps://github.com/ymatts/RoDiCE.


title: SLIDR and SLOPPR: Flexible identification of spliced leader trans-splicing and prediction of eukaryotic operons from RNA-Seq data

abstract:
BackgroundSpliced leader (SL) trans-splicing replaces the 5 end of pre-mRNAs with the spliced leader, an exon derived from a specialised non-coding RNA originating from elsewhere in the genome. This process is essential for resolving polycistronic pre-mRNAs produced by eukaryotic operons into monocistronic transcripts. SL trans-splicing and operons may have independently evolved multiple times throughout Eukarya, yet our understanding of these phenomena is limited to only a few well-characterised organisms, most notably C. elegans and trypanosomes. The primary barrier to systematic discovery and characterisation of SL trans-splicing and operons is the lack of computational tools for exploiting the surge of transcriptomic and genomic resources for a wide range of eukaryotes.

ResultsHere we present two novel pipelines that automate the discovery of SLs and the prediction of operons in eukaryotic genomes from RNA-Seq data. SLIDR assembles putative SLs from 5 read tails present after read alignment to a reference genome or transcriptome, which are then verified by interrogating corresponding SL RNA genes for sequence motifs expected in bona fide SL RNA molecules. SLOPPR identifies RNA-Seq reads that contain a given 5 SL sequence, quantifies genomewide SL trans-splicing events and predicts operons via distinct patterns of SL trans-splicing events across adjacent genes. We tested both pipelines with organisms known to carry out SL trans-splicing and organise their genes into operons, and demonstrate that 1) SLIDR correctly detects expected SLs and often discovers novel SL variants; 2) SLOPPR correctly identifies functionally specialised SLs, correctly predicts known operons and detects plausible novel operons.

ConclusionsSLIDR and SLOPPR are flexible tools that will accelerate research into the evolutionary dynamics of SL trans-splicing and operons throughout Eukarya and improve gene discovery and annotation for a wide-range of eukaryotic genomes. Both pipelines are implemented in Bash and R and are built upon readily available software commonly installed on most bioinformatics servers. Biological insight can be gleaned even from sparse, low-coverage datasets, implying that an untapped wealth of information can be derived from existing RNA-Seq datasets as well as from novel full-isoform sequencing protocols as they become more widely available.