title: Simulated poaching affects global connectivity and efficiency in social networks of African savanna elephants - an exemplar of how human disturbance impacts group-living species

abstract:
Selective harvest, such as poaching, impacts group-living animals directly through mortality of individuals with desirable traits, and indirectly by altering the structure of their social networks. Understanding the relationship between the structural network changes and group performance in wild animals remains an outstanding problem. To address this knowledge gap, we evaluate the immediate effect of disturbance on group sociality in African savanna elephants -- an example, group-living species threatened by poaching. Drawing on static association data from one free ranging population, we constructed 100 virtual networks; performed a series of experiments  poaching the oldest, socially central or random individuals; and quantified the immediate change in the theoretical indices of network connectivity and efficiency of social diffusion. Although the virtual networks never broke down, targeted elimination of the socially central conspecifics, regardless of age, decreased network connectivity and efficiency. These findings hint at the need to further study resilience by modeling network reorganization and interaction-mediated socioecological learning, empirical data permitting. Our work is unique in quantifying connectivity together with global efficiency in multiple virtual networks that represent the sociodemographic diversity of elephant populations likely found in the wild. The basic design of our simulation platform makes it adaptable for hypothesis testing about the consequences of anthropogenic disturbance or lethal management on social interactions in a variety of group-living species with limited, real-world data.

Author SummaryWe consider the immediate response of animal groups to human disturbance by using the African savanna elephant as an example of a group-living species threatened by poaching. Previous research in one elephant population showed that poaching-induced mortality reduced social interaction among distantly related elephants, but not among close kin. Whether this type of resilience indicates that affected populations function similarity before and after poaching is an open problem. Understanding it is important because poaching often targets the largest and most socially and ecologically experienced group members. Drawing on empirical association data, we simulated poaching in 100 virtual elephant populations and eliminated the most senior or sociable members. Targeted poaching of sociable conspecifics was more impactful. Although it did not lead to population breakdown, it hampered theoretical features of interspecific associations that in other systems have been associated with group cohesion and the efficiency of transferring social information. Our findings suggest that further inquiry into the relationship between resilience to poaching and group performance is warranted. In addition, our simulation platform offers a generalizable basis for hypothesis testing in other social species, wild or captive, subject to exploitation by humans.


title: Local coupling between sleep spindles and slow oscillations supports the stabilization of motor memories

abstract:
Recent studies from us and others suggest that traditionally declarative structures (e.g., hippocampus) mediate some aspects of the encoding and consolidation of procedural memories. This evidence points to the existence of converging physiological pathways across memory systems. Here, we examined whether the coupling between slow oscillations (SO) and spindles, a mechanism well established in the consolidation of declarative memories, is relevant for the stabilization of human motor memories. To this aim, we conducted an EEG study in which we quantified various parameters of these oscillations during a night of sleep that took place immediately after learning a visuomotor adaptation task. We hypothesized that if this coupling is instrumental to motor memory consolidation then spindles locked to the active phase of a slow oscillation would predict long-term memory. We found that visuomotor adaptation increased the overall density of fast ([≥]12 Hz) but not slow (<12Hz) spindles during NREM3. This modulation was manifested rather locally, over the hemisphere contralateral to the trained hand. Although motor learning did not affect the density of SOs, it substantially enhanced the number of fast spindles locked to the active phase of SOs. The fact that only coupled spindles of the left hemisphere predicted long-term memory overnight, points to the precise phase relationship between these oscillations as a fundamental signature of motor memory consolidation. Our work provides evidence in favor of a common mechanism at the basis of the stabilization of declarative and non-declarative memories.

Significance StatementEver since the discovery of memory systems, the study of the mechanisms supporting the consolidation of declarative and procedural memories has progressed somewhat in parallel. In the last few years, however, this framework is starting to change. We now know that structures originally thought of as purely declarative, such as the hippocampus, participate in the consolidation of procedural tasks. Here, we show that sleep modulates the stabilization of motor memories through a mechanism involved in the consolidation of declarative memories, based on the local synchrony between fast sleep spindles and slow oscillations. The fact that only coupled -but not uncoupled- spindles of the contralateral hemisphere predicted long-term memory supports a role of this association in the consolidation of motor memories.

category: neuroscience


title: Cognitive deficits found in a pro-inflammatory state are independent of ERK 1/2 signaling in the murine brain hippocampus treated with Shiga toxin 2 from enterohemorrhagic Escherichia Coli

abstract: Shiga toxin 2 (Stx2) from enterohemorrhagic Escherichia coli (EHEC) produces hemorrhagic colitis, hemolytic uremic syndrome (HUS) and acute encephalopathy. The mortality rate in HUS increases significantly when the central nervous system (CNS) is involved. Besides, EHEC also releases lipopolysaccharide (LPS). Many reports have described cognitive dysfunctions in HUS patients, the hippocampus being one of the brain areas targeted by EHEC infection. In this context, a translational murine model of encephalopathy was employed to establish the deleterious effects of Stx2 and the contribution of LPS in the hippocampus. Results demonstrate that systemic administration of a sublethal dose of Stx2 reduced memory index and produced depression like behavior, pro-inflammatory cytokine release and NF-kB activation independent of the ERK 1/2 signaling pathway. On the other hand, LPS activated NF-kB dependent on ERK 1/2 signaling pathway. Cotreatment of Stx2 with LPS aggravated the pathologic state, while dexamethasone treatment succeeded in preventing behavioral alterations. Our present work suggests that the use of drugs such as corticosteroids or NF-kB signaling inhibitors may serve as neuroprotectors from EHEC infection.

category: pathology


title: Synchrony between daily rhythms of malaria parasites and hosts is driven by an essential amino acid

abstract: Rapid asexual replication of blood stage malaria parasites is responsible for the severity of disease symptoms and fuels the production of transmission forms. That malaria parasite species coordinate their cycles of asexual replication with daily rhythms of their host was discovered in the Hippocratic era, but how and why this occurs is enigmatic. Here, we demonstrate that the Plasmodium chabaudis schedule for asexual replication can be orchestrated by a isoleucine, metabolite provided to the parasite in periodic manner due to the hosts rhythmic intake of food. First, we identify nutrients with daily rhythms in the blood that match the timing of rhythms in both host feeding and the developmental schedule of asexually replicating parasites. We hypothesise that if parasites set their own developmental schedule, they should use a time-of-day cue that is a factor they cannot generate endogenously at any time-of-day, or scavenge in a round-the-clock manner. Our large-scale metabolomics experiment reveals that only one metabolite - the amino acid isoleucine - fits these criteria. Second, further experiments reveal that parasites alter the developmental schedule of asexual stages in response to isoleucine provision and withdrawal in the manner consistent with it acting as a time-cue. Specifically, parasites respond to isoleucine loss by slowing development. This is a parasite strategy rather than the consequences of an imposed constraint, because unlike when parasites are deprived of other essential nutrients, they suffer no apparent costs in the absence of isoleucine. Overall, our data suggest parasites can use the daily rhythmicity of blood-isoleucine concentration to synchronise asexual development with the availability of isoleucine, and potentially other resources, that arrive in the blood in a periodic manner due to the hosts daily feeding-fasting cycle. Identifying both how and why parasites keep time opens avenues for interventions; interfering with the parasites time-keeping mechanism may stall replication, increasing the efficacy of drugs and immune responses, and could also prevent parasites from entering dormancy to tolerate drugs.

category: microbiology


title: Improved genetic prediction of complex traits from individual-level data or summary statistics

abstract: Most existing tools for constructing genetic prediction models begin with the assumption that all genetic variants contribute equally towards the phenotype. However, this represents a suboptimal model for how heritability is distributed across the genome. Therefore, we develop prediction tools that allow the user to specify the heritability model. We compare individual-level data prediction tools using 14 UK Biobank phenotypes; our new tool LDAK-Bolt-Predict outperforms the existing tools Lasso, BLUP, Bolt-LMM and BayesR for all 14 phenotypes. We compare summary statistic prediction tools using 225 UK Biobank phenotypes; our new tool LDAK-BayesR-SS outperforms the existing tools lassosum, sBLUP, LDpred and SBayesR for 223 of the 225 phenotypes. The increase in prediction accuracy from improving the heritability model tends to be substantial. For example, when using LDAK-Bolt-Predict, the proportion of phenotypic variance explained increased by on average 14% (range 5-29%), equivalent to increasing the sample size by a quarter.

category: genetics


title: Gene set enrichment analysis for genome-wide DNA methylation data

abstract: DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalisation and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

category: bioinformatics


title: Avalanche criticality in individuals, fluid intelligence and working memory

abstract: The critical brain hypothesis suggests that efficient neural computation can be realized through dynamics of the brain characterized by scale-free avalanche activities. However, the relation between human cognitive performance and the avalanche criticality in large-scale brain networks remains unclear. In this study, we analyzed the mean synchronization and synchronization entropy of blood oxygenation level signals from resting-state fMRI. We found that the scale-free avalanche activity was associated with intermediate synchronization and maximal synchronization entropy. The complexity of functional connectivity, as well as structure-function coupling, is maximized by criticality, which is consistent with theoretical predictions. We observed order-disorder phase transitions in resting-state brain dynamics and found that there were longer times spent in the subcritical regime. These results support the hypothesis that large-scale brain networks lie in the vicinity of a critical point. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance, and found these regions were located in the prefrontal cortex and inferior parietal cortex, which are believed to be important nodes of brain networks underlying human intelligence. Our results reveal the role that avalanche criticality plays in cognitive performance, and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.


title: Click evoked Middle Ear Muscle Reflex: Spectral and Temporal Aspects

abstract: This study describes a time series-based method of middle ear muscle reflex (MEMR) detection using bilateral clicks. Although many methods can detect changes in the OAE evoking stimulus to monitor the MEMR, they do not discriminate between true MEMR-mediated vs. artifactual changes in the stimulus. We measured MEMR in 20 young clinically normal hearing individuals using 1-second-long click trains presented at six levels (65 to 95 dB peak-to-peak SPL in 6 dB steps). Changes in the stimulus levels over the 1 second period were well-approximated by two-term exponential functions. The magnitude of ear canal pressure changes due to MEMR increased monotonically as a function of click level but non-monotonically with frequency when separated into 1/3rd-octave wide bands between 1 and 3.2 kHz. MEMR thresholds estimated using this method were lower than that obtained from a clinical tympanometer in [~]94% of the participants. A time series-based method, along with statistical tests, may provide additional confidence in detecting the MEMR. MEMR effects were smallest at 2 kHz, between 1 and 3.2 kHz, which may provide avenues for minimizing the MEMR influence while measuring other responses (e.g., the medial olivocochlear reflex).


title: An Easy-to-Fabricate Cell Stretcher Reveals Density-Dependent Mechanical Regulation of Collective Cell Movements in Epithelia

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSIntroductionC_ST_ABSMechanical forces regulate many facets of cell and tissue biology. Studying the effects of forces on cells requires real-time observations of single- and multi-cell dynamics in tissue models during controlled external mechanical input. Many of the existing devices used to conduct these studies are costly and complicated to fabricate, which reduces the availability of these devices to many laboratories.

MethodsWe show how to fabricate a simple, low-cost, uniaxial stretching device, with readily available materials and instruments that is compatible with high-resolution time-lapse microscopy of adherent cell monolayers. In addition, we show how to construct a pressure controller that induces a repeatable degree of stretch in monolayers, as well as a custom MATLAB code to quantify individual cell strains.

ResultsAs an application note using this device, we show that uniaxial stretch slows down cellular movements in a mammalian epithelial monolayer in a cell density-dependent manner. We demonstrate that the effect on cell movement involves the relocalization of myosin downstream of Rho-associated protein kinase (ROCK).

ConclusionsThis mechanical device provides a platform for broader involvement of engineers and biologists in this important area of cell and tissue biology. We used this device to demonstrate the mechanical regulation of collective cell movements in epithelia.

category: bioengineering


title: Preexisting memory CD4 T cells in nÏave individuals confer robust immunity upon hepatitis B vaccination

abstract: Antigen recognition through the T cell receptor (TCR) {beta} heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naive T cells with high specificity to expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naive hosts. In this study, we use high-throughput sequencing of memory CD4 TCR{beta} repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCR{beta} sequence patterns into a hepatitis B vaccine specific model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination.

category: immunology


title: Using Multilayer Heterogeneous Net-works to Infer Functions of Phosphorylated Sites

abstract:
1Mass spectrometry-based quantitative phosphoproteomics has become an essential approach in the study of cellular processes such as signaling. Commonly used methods to analyze phosphoproteomics datasets depend on generic, gene-centric annotations such as Gene Ontology terms which do not account for the function of a protein in a particular phosphorylation state. Analysis of phosphoproteomics data is hampered by a lack of phosphorylated site-specific annotations. We propose a method that combines shotgun phosphoproteomics data, protein-protein interactions, and functional annotations into a heterogeneous multilayer network. Phosphorylation sites are associated to potential functions using a random walk on heterogeneous network (RWHN) algorithm. We validated our approach against a model of the MAPK/ERK pathway and functional annotations from PhosphoSite Plus and were able to associate differentially regulated sites on the same proteins to their previously described specific functions. We further tested the algorithm on three previously published datasets and were able to reproduce their experimentally validated conclusions and to associate phosphorylation sites with known functions based on their regulatory patterns. Our approach provides a refinement of commonly used analysis methods and accurately predicts context-specific functions for sites with similar phosphorylation profiles.

For table of contents onlyWe confirm that the eTOC figure contains original material drawn by the authors.

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title: On stability of Canonical Correlation Analysis and Partial Least Squares with application to brain-behavior associations

abstract: Associations between datasets, each comprising many features, can be discovered through multivariate methods like Canonical Correlation Analysis (CCA) or Partial Least Squares (PLS). Application of CCA/PLS to high-dimensional datasets raises critical questions about reliability and interpretability. To study this, we developed a generative modeling framework to simulate synthetic datasets, parameterized by dimensionality, variance structure, and association strength. We found that CCA/PLS associations could be highly inaccurate when the number of samples per feature is relatively small. For PLS, profiles of feature weights exhibit detrimental bias toward leading principal component axes. We confirmed these trends in state-of-the-art neuroimaging datasets, Human Connectome Project (n{approx}1000) and UK Biobank (n=20000), finding that only the latter comprised sufficient samples for stable estimates. Analysis of the neuroimaging literature using CCA to map brain-behavior relationships revealed also that the commonly employed sample sizes yield unstable CCA solutions. Finally, we provide a calculator of dataset properties required for CCA/PLS stability. Collectively, we characterize how to limit detrimental effects of overfitting on CCA/PLS stability, and provide recommendations for future studies.


title: A physical theory of movement in small animals

abstract: All animal behaviour must ultimately be governed by physical laws. As a basis for understanding the physics of behaviour in a simple system, we here develop an effective theory for the motion of the larval form of the fruitfly Drosophila melanogaster, and compare it against a quantitative analysis of the real animals behaviour. We first define a set of fields which quantify stretching, bending, and twisting along the larvas antero- posterior axis, and then perform a search in the space of possible theories that could govern the long-wavelength physics of these fields, using a simplified approach inspired by the renormalisation group. Guided by symmetry considerations and stability requirements, we arrive at a unique, analytically tractable free-field theory with a minimum of free parameters. Unexpectedly, we are able to explain a wide-spectrum of features of Drosophila larval behaviour by applying equilibrium statistical mechanics: our theory closely predicts the animals postural modes (eigenmaggots), as well as distributions and trajectories in the postural mode space across several behaviours, including peristaltic crawling, rolling, self-righting and unbiased substrate exploration. We explain the low-dimensionality of postural dynamics via Boltzmann suppression of high frequency modes, and also propose and experimentally test, novel predictions on the relationships between different forms of body deformation and animal behaviour. We show that crawling and rolling are dominated by similar symmetry properties, leading to identical dynamics/statistics in mode space, while rolling and unbiased exploration have a common dominant timescale. Furthermore, we are able to demonstrate that self-righting behaviour occurs continuously throughout substrate exploration, owing to the decoupling of stretching, bending, and twisting at low energies. Together, our results demonstrate that relatively simple effective physics can be used to explain and predict a wide range of animal behaviours.

category: biophysics


title: The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

abstract: Bulk transcriptomic studies have defined classical and basal-like gene expression subtypes in pancreatic ductal adenocarcinoma (PDAC) that correlate with survival and response to chemotherapy; however, the underlying mechanisms that govern these subtypes and their heterogeneity remain elusive. Here, we performed single-cell RNA-sequencing of 23 metastatic PDAC needle biopsies and matched organoid models to understand how tumor cell-intrinsic features and extrinsic factors in the tumor microenvironment (TME) shape PDAC cancer cell phenotypes. We identify a novel cancer cell state that co-expresses basal-like and classical signatures, demonstrates upregulation of developmental and KRAS-driven gene expression programs, and represents a transitional intermediate between the basal-like and classical poles. Further, we observe structure to the metastatic TME supporting a model whereby reciprocal intercellular signaling shapes the local microenvironment and influences cancer cell transcriptional subtypes. In organoid culture, we find that transcriptional phenotypes are plastic and strongly skew toward the classical expression state, irrespective of genotype. Moreover, we show that patient-relevant transcriptional heterogeneity can be rescued by supplementing organoid media with factors found in the TME in a subtype-specific manner. Collectively, our study demonstrates that distinct microenvironmental signals are critical regulators of clinically relevant PDAC transcriptional states and their plasticity, identifies the necessity for considering the TME in cancer modeling efforts, and provides a generalizable approach for delineating the cell-intrinsic versus -extrinsic factors that govern tumor cell phenotypes.

category: cancer biology


title: Facilitation and biodiversity jointly drive mutualistic networks

abstract:
O_LIFacilitation by nurse plants increases understorey diversity and supports ecological communities. In turn, biodiversity shapes ecological networks and enhances ecosystem functioning. However, whether and how facilitation and increased biodiversity jointly influence community structure and ecosystem functioning remains unclear.
C_LIO_LIWe performed a field experiment disentangling the relative contribution of nurse plants and increasing understorey plant diversity in driving pollination interactions. Both the presence of nurse shrubs as well as increased understorey plant diversity increased pollinator diversity and visitation rates. While nurse and understorey diversity effects on pollinator visitation rates did not interact, the effects of increasing understorey plant diversity on pollinator diversity were stronger in the absence than in the presence of shrubs, meaning that nurse shrubs attenuated the effects of high understorey diversity and buffered the effects of low understorey diversity.
C_LIO_LIWe also found positive complementarity effects among understorey species as well as complementarity between nurse plants and understorey species at high diversity. Results also indicate negative selection effects, suggesting that species with generally few pollinators benefit the most in the polyculture, while a species (possibly the nurse plant) with generally lots of pollinators does not. The corresponding changes in pollination networks with the experimental treatments were due to both changes in the frequency of visits and turnover in pollinator community composition.
C_LIO_LISynthesis Plant-plant facilitative systems, where a nurse plant increases understorey plant diversity, are common in stressful environments. Here, we show that these facilitative systems positively influence mutualistic interactions with pollinators via both direct nurse effects and indirect positive effects of increasing plant diversity.
C_LIO_LIConserving and supporting nurse plant systems is crucial not only for maintaining plant diversity but also for supporting ecosystem functions and services.
C_LI

category: ecology


title: Frequent lineage-specific substitution rate changes support an episodic model for protein evolution

abstract: Since the inception of the molecular clock model for sequence evolution, the investigation of protein divergence has revolved around the question of a more or less constant rate of overall sequence information change. Although anomalies in clock-like divergence are described for some proteins, nowadays, the assumption of a constant decay rate for a given protein family is taken as the null model for protein evolution. Still, so far, a systematic test of this null model has not been done at a genome-wide scale despite the databases enormous growth. We focus here on divergence rate comparisons between closely related lineages, since this allows clear orthology assignments by synteny and unequivocal alignments, which are crucial for the determination of substitution rate changes. Thus, we generated a high-confidence dataset of syntenic orthologs from four ape species, including humans. Further analysis revealed that despite the appearance of an overall clock-like substitution pattern, a substantial number of proteins show lineage-specific acceleration and deceleration in divergence rates, or combinations of both in different lineages. Interestingly, when aggregated, even the families showing large lineage-specific rate perturbations can show overall rate equality. Our analysis uncovers a much more dynamic history of substitution rate changes in protein families. Which invalidates a pan-genome null model of constant decay, on the one hand, but remains compatible with the existing notion that aggregated data can be reliably used to estimate species splitting time. Ultimately, our data shows that a null model of constant change is not suitable to predict the evolutionary trajectories of individual proteins.

category: evolutionary biology


title: Medial prefrontal activity at encoding determines enhanced recognition of threatening faces after 1.5 years

abstract: Studies demonstrated that faces with threatening emotional expressions are better remembered than non-threatening faces. However, whether this memory advantage persists over years and which neural systems underlie such an effect remains unknown. Here, we investigated recognition of incidentally encoded faces with angry, fearful, happy, sad and neutral expressions over >1.5 years (N= 89). Univariate analyses showed that threatening faces (angry, fearful) were better recognized than happy and neutral faces after >1.5 years, and that the threat-related memory enhancement was driven by forgetting of non-threatening faces. Multivariate principal component analysis (PCA) confirmed the discriminative performance between threatening and non-threatening faces. With an innovative Behavioral Pattern Similarity Analysis (BPSA) approach and functional magnetic resonance imaging (fMRI) acquisition during encoding, we further found that the long-term memory advantage for threatening faces were underpinned by differential neural encoding in the left inferior occipital gyrus (IOG) and right ventromedial prefrontal/orbitofrontal cortex (vmPFC/OFC). Our study provides the first evidence that threatening facial expressions lead to persistent face recognition over periods of >1.5 years and differential encoding-related activity in the visual cortex and medial prefrontal cortex may underlie this effect.


title: Population modeling with machine learning can enhance measures of mental health

abstract:
BackgroundBiological aging is revealed by physical measures, e.g., DNA probes or brain scans. Instead, individual differences in mental function are explained by psychological constructs, e.g., intelligence or neuroticism. These constructs are typically assessed by tailored neuropsychological tests that build on expert judgement and require careful interpretation. Could machine learning on large samples from the general population be used to build proxy measures of these constructs that do not require human intervention?

ResultsHere, we built proxy measures by applying machine learning on multimodal MR images and rich sociodemographic information from the largest biomedical cohort to date: the UK Biobank. Objective model comparisons revealed that all proxies captured the target constructs and were as useful, and sometimes more useful than the original measures for characterizing real-world health behavior (sleep, exercise, tobacco, alcohol consumption). We observed this complementarity of proxy measures and original measures when modeling from brain signals or sociodemographic data, capturing multiple health-related constructs.

ConclusionsPopulation modeling with machine learning can derive measures of mental health from brain signals and questionnaire data, which may complement or even substitute for psychometric assessments in clinical populations.

Key PointsO_LIWe applied machine learning on more than 10.000 individuals from the general population to define empirical approximations of health-related psychological measures that do not require human judgment.
C_LIO_LIWe found that machine-learning enriched the given psychological measures via approximation from brain and sociodemographic data: Resulting proxy measures related as well or better to real-world health behavior than the original measures.
C_LIO_LIModel comparisons showed that sociodemographic information contributed most to characterizing psychological traits beyond aging.
C_LI


title: The Population Genetics of Collateral Resistance and Sensitivity

abstract: Resistance mutations against one drug can elicit collateral sensitivity against other drugs. Multi-drug treatments exploiting such trade-offs can help slow down the evolution of resistance. However, if mutations with diverse collateral effects are available, a treated population may evolve either collateral sensitivity or collateral resistance. How to design treatments robust to such uncertainty is unclear. We show that many resistance mutations in Escherichia coli against various antibiotics indeed have diverse collateral effects. We propose to characterize such diversity with a joint distribution of fitness effects (JDFE) and develop a theory for describing and predicting collateral evolution based on simple statistics of the JDFE. We show how to robustly rank drug pairs to minimize the risk of collateral resistance and how to estimate JDFEs. In addition to practical applications, these results have implications for our understanding of evolution in variable environments.


title: Highly potent anti-SARS-CoV-2 multivalent DARPin therapeutic candidates

abstract: Globally accessible therapeutics against SARS-CoV-2 are urgently needed. Here, we report the generation of the first anti-SARS-CoV-2 DARPin molecules with therapeutic potential as well as rapid large-scale production capabilities. Highly potent multivalent DARPin molecules with low picomolar virus neutralization efficacies were generated by molecular linkage of three different monovalent DARPin molecules. These multivalent DARPin molecules target various domains of the SARS-CoV-2 spike protein, thereby limiting possible viral escape. Cryo-EM analysis of individual monovalent DARPin molecules provided structural explanations for the mode of action. Analysis of the protective efficacy of one multivalent DARPin molecule in a hamster SARS-CoV-2 infection model demonstrated a significant reduction of pathogenesis. Taken together, the multivalent DARPin molecules reported here, one of which has entered clinical studies, constitute promising therapeutics against the COVID-19 pandemic.


title: Local and substrate-specific S-palmitoylation determines subcellular localization of Gαo

abstract: Peripheral membrane proteins (PMPs) associate with cellular membranes through post-translational modifications like S-palmitoylation. The Golgi apparatus is generally viewed as the transitory station where palmitoyl acyltransferases (PATs) modify PMPs, which are then transported to their ultimate destinations such as the plasma membrane (PM). However, little substrate specificity among the many PATs has been determined. Here we describe the inherent partitioning of Go - -subunit of heterotrimeric Go proteins - to PM and Golgi, independent from Golgi-to-PM transport. A minimal code within Go N-terminus governs its compartmentalization and re-coding produces G protein versions with shifted localization. We establish the S-palmitoylation at the outer nuclear membrane assay ("SwissKASH") to probe substrate specificity of PATs in intact cells. With this assay, we show that PATs localizing to different membrane compartments display remarkable substrate selectivity, which is the basis for PMP compartmentalization. Our findings uncover a mechanism governing protein localization and establish the basis for innovative drug discovery.

category: cell biology


title: Cortical Magnification in Human Visual Cortex Parallels Task Performance around the Visual Field

abstract: Human vision has striking radial asymmetries, with performance on many tasks varying sharply with stimulus polar angle. Performance is generally better on the horizontal than vertical meridian, and on the lower than upper vertical meridian, and these asymmetries decrease gradually with deviation from the vertical meridian. Here we report cortical magnification at a fine angular resolution around the visual field. This precision enables comparisons between cortical magnification and behavior, between cortical magnification and retinal cell densities, and between cortical magnification in twin pairs. We show that cortical magnification in human primary visual cortex, measured in 163 subjects, varies substantially around the visual field, with a pattern similar to behavior. These radial asymmetries in cortex are larger than those found in the retina, and they are correlated between monozygotic twin pairs. These findings indicate a tight link between cortical topography and behavior, and suggest that visual field asymmetries are partly heritable.


title: Prenatal Stress Dysregulates Resting-State Functional Connectivity and Sensory Motifs

abstract: Prenatal stress (PS) can impact fetal brain structure and function and contribute to higher vulnerability to neurodevelopmental and neuropsychiatric disorders. To understand how PS alters evoked and spontaneous neocortical activity and intrinsic brain functional connectivity, mesoscale voltage imaging was performed in adult C57BL/6NJ mice that had been exposed to auditory stress on gestational days 12-16, the age at which neocortex is developing. PS mice had a four-fold higher basal corticosterone level and reduced amplitude of cortical sensory-evoked responses to visual, auditory, whisker, forelimb, and hindlimb stimuli. Relative to control animals, PS also led to a general reduction of resting-state functional connectivity, as well as reduced inter-modular connectivity, enhanced intra-modular connectivity, and altered frequency of auditory and forelimb spontaneous sensory motifs. These resting-state changes resulted in a cortical connectivity pattern featuring disjoint but tight modules and a decline in network efficiency. The findings demonstrate that cortical connectivity is sensitive to PS and exposed offspring may be at risk for adult stress-related neuropsychiatric disorders.


title: Single particle-resolution fluorescence microscopy of nanoplastics

abstract:
Understanding of nanoplastic prevalence and toxicology is limited by imaging challenges resulting from their small size. Fluorescence microscopy is widely applied to track and identify microplastics in laboratory studies and environmental samples. However, conventional fluorescence microscopy, due to diffraction, lacks the resolution to precisely localize nanoplastics in tissues, distinguish them from free dye, or quantify them in environmental samples. To address these limitations, we developed techniques to label nanoplastics for imaging with Stimulated Emission Depletion (STED) microscopy to achieve resolution at an order of magnitude superior to conventional fluorescence microscopy. These techniques include (1) passive sorption; (2) swell incorporation; and (3) covalent coupling of STED-compatible fluorescence dyes to nanoplastics. We demonstrate that our labeling techniques, combined with STED microscopy, can be used to resolve nanoplastics of different shapes and compositions as small as 50 nm. The longevity of the dye labeling is demonstrated in different media and conditions of biological and environmental relevance. We also test STED imaging of nanoplastics in exposure experiments with the model worm C. elegans. These techniques will allow more precise localization and quantification of nanoplastics in complex matrices.

SynopsisWe show that Stimulated Emission Depletion (STED) microscopy can be used to image single nanoplastics of different compositions and shapes. This will allow researchers to study environmentally-relevant nanoplastics and their interactions with organisms in relevant exposure scenarios.

TOC Graphic O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY


title: On the joint effect of endogenous spatial attention and defocus blur on acuity: attentional limit to the resolving power of the eye

abstract:
Defocus blur and spatial attention both act on our ability to see clearly over time. However, it is currently unknown how these two factors interact because studies on acuity resolution only focused on the separate effects of attention and defocus blurs. In this study, resolution acuity was measured along the diagonal 135{degrees}/315{degrees} with horizontal, at 8{degrees} eccentricity for clear and blur Landolt C images under various manipulations of covert endogenous attention. We observe that attention not just improves the resolution of clear stimuli, but also modulates the resolution of defocused stimuli for compensating the loss of resolution caused by retinal blur. Our results show, however, that as the degree of attention decreases, the differences between clear and blurred images largely diminish, thus limiting the benefit of an image quality enhancement. It also appeared that attention tends to enhance the resolution of clear images more than blurred targets, suggesting potential variations in the gain of vision correction with the level of attention. This demonstrates that the interaction between spatial attention and focus plays a role in the way we see things. In view of these findings, the development of adaptive (neuro-optical) interventions, which adjust the eyes focus to attention, may hold promise.

Significance statementVisual technologies are now attaining a degree of extreme sophistication and diversity, which allows more comprehensive, but often complex manipulations of the optical image formed onto the back of the eye. It is therefore an enigma how those fine and immersive manipulations of the sensory environment are integrated in the brain. In this study, we show that the resolving power of the eye can depend complexly on the interaction between spatial attention and focus. This discovery suggests that perception might be advantageously guided by technologies tailoring optical focus to individual attentional patterns.

Graphical abstract

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org.highwire.dtl.DTLVardef@de73b7org.highwire.dtl.DTLVardef@7ef3d3org.highwire.dtl.DTLVardef@b9a80dorg.highwire.dtl.DTLVardef@c8201e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Proposed neuro-optical mechanism of transformation of stimulus by spatial attention and blur.


title: eQTpLot: a user-friendly R package for the visualization and colocalization of eQTL and GWAS signals

abstract:
Genomic studies increasingly integrate expression quantitative trait loci (eQTL) information into their analysis pipelines, but few tools exist for the visualization of colocalization between eQTL and GWAS results. Those tools that do exist are limited in their analysis options, and do not integrate eQTL and GWAS information into a single figure panel, making the visualization of colocalization difficult.

To address this issue, we developed the intuitive and user-friendly R package eQTpLot. eQTpLot takes as input standard GWAS and eQTL summary statistics, and optional pairwise LD information, to generate a series of plots visualizing colocalization, correlation, and enrichment between eQTL and GWAS signals for a given gene-trait pair. With eQTpLot, investigators can easily generate a series of customizable plots clearly illustrating, for a given gene-trait pair: 1) colocalization between GWAS and eQTL signals, 2) correlation between GWAS and eQTL p-values, 3) enrichment of eQTLs among trait-significant variants, 4) the LD landscape of the locus in question, and 5) the relationship between the direction of effect of eQTL signals and the direction of effect of colocalizing GWAS peaks. These clear and comprehensive plots provide a unique view of eQTL-GWAS colocalization, allowing for a more complete understanding of the interaction between gene expression and trait associations.

In summary, eQTpLot provides a unique, user-friendly, and intuitive means of visualizing eQTL and GWAS signal colocalization, incorporating novel features not found in other eQTL visualization software. We believe eQTpLot will prove a useful tool for investigators seeking a convenient and customizable visualization of eQTL and GWAS data colocalization.

Availability and Implementationthe eQTpLot R package and tutorial are available at https://github.com/RitchieLab/eQTpLot


title: Induction of selective cell death in HIV-1-infected cells by DDX3 inhibitors leads to depletion of the inducible reservoir

abstract: An innovative approach to eliminate HIV-1-infected cells emerging out of latency, the major hurdle to HIV-1 cure, is to pharmacologically reactivate viral expression and concomitantly trigger intracellular pro-apoptotic pathways in order to selectively induce cell death (ICD) of infected cells, without reliance on the extracellular immune system. In this work we demonstrate the effect of DEAD-box polypeptide 3, X-Linked (DDX3) inhibitors on selectively inducing cell death in latent HIV-1-infected cell lines, primary CD4+ T cells and in CD4+ T cells from cART-suppressed people living with HIV-1 (PLWHIV). RNA sequencing analysis revealed that while overall gene expression was minimally dysregulated, DDX3 inhibition in independent donor CD4+ T cells led to significant downregulation of BIRC5 and HSPB1A, genes critical to cell survival during HIV-1 infection. We used single-cell FISH-Flow technology to characterise latency reversal and the contribution of viral RNA to inducing cell death; pharmacological targeting of DDX3 induced HIV-1 RNA expression, resulting in phosphorylation of IRF3, upregulation of IFN{beta} and selective induction of apoptosis in viral RNA-expressing CD4+ T cells from PLWHIV but not bystander cells. DDX3 inhibitor treatment of CD4+ T cells from PLWHIV in an in vitro culture model over five days resulted in an approximately 50% reduction of the inducible latent HIV-1 reservoir as determined by quantitation of CA HIV-1 RNA, by TILDA, as well as by FISH-Flow technology. Our data support the translation of DDX3 inhibitor class compounds into HIV-1 curative strategies and provide proof of concept for pharmacological reversal of latency coupled to induction of apoptosis towards elimination of the inducible reservoir.


title: ALS-FUS mutation affects the activities of HuD/ELAVL4 and FMRP leading to axon phenotypes in motoneurons

abstract: Mutations in the RNA-binding protein (RBPs) FUS have been genetically associated with the motoneuron disease amyotrophic lateral sclerosis (ALS). Using both human induced pluripotent stem cells and mouse models, we found that FUS-ALS causative mutations affect the activity of two relevant RBPs with important roles in neuronal RNA metabolism: HuD/ELAVL4 and FMRP. Mechanistically, mutant FUS leads to upregulation of HuD protein levels through competition with FMRP for HuD mRNA 3UTR binding. In turn, increased HuD levels overly stabilize the transcript levels of its targets, NRN1 and GAP43. As a consequence, mutant FUS motoneurons show increased axon branching and growth upon injury, which could be rescued by dampening NRN1 levels. Since similar phenotypes have been previously described in SOD1 and TDP-43 mutant models, increased axonal growth and branching might represent broad early events in the pathogenesis of ALS.


title: Boosting L-type Ca2+ channel activity in tuberous sclerosis mitigates excess glutamate receptors and seizures

abstract:
Tuberous sclerosis complex (TS) is a dominant, multisystem disorder with devastating neurological symptoms. Approximately 85% of TS patients suffer from epilepsy over their lifespan and roughly 25-50% of those patients develop Autism Spectrum Disorder (1, 2). Current seizure therapies are effective in some, but not all, and often have significant risk factors associated with their use (1, 3). Thus, there is a critical need for new medication development or drug repositioning. Herein, we leveraged proteomic signatures of epilepsy and ASD, often comorbid in TS, to utilize an in silco approach to identify new drug therapies for TS-related seizures. We have discovered that activation of L-type voltage dependent calcium channels (L-VDCC) by Bay-K8644 (BayK) in a preclinical mouse model of TS rescues the excess expression of ionotropic, AMPA-subtype glutamate (GluA) receptors. As added proof of BayK working through L-VDCC to regulate GluA levels, we found that increasing expression of alpha2delta2 (2{delta}2), an auxiliary calcium channel subunit that boosts L-VDCC surface expression, similarly lowers the surface expression of dendritic GluA in TS. These BayK-induced molecular alterations may potentially improve the quality of life of humans suffering from TS.

Significance StatementCausal mechanisms of Tuberous Sclerosis (TS)-associated neurological disorders are under-characterized and treatment options are lacking. Using a computational approach of mTOR/DJ-1 target mRNAs to predict new medications, we report that boosting L-type voltage-dependent Ca2+ channel (L-VDCC) activity in a preclinical TS mouse model that exhibits a deficit in dendritic L-VDCC activity ameliorates key molecular pathologies that are predicted to underlie seizures. Restoring the mTOR/DJ-1 pathway upstream of L-VDCC, therefore, may serve as a new therapeutic avenue to mitigate seizures and mortality in TS.


title: Boosting L-type Ca2+ channel activity in tuberous sclerosis mitigates excess glutamate receptors


title: Neural tracking of the fundamental frequency of the voice: the effect of voice characteristics

abstract:
Traditional electrophysiological methods to study temporal auditory processing of the fundamental frequency of the voice (f0) often use unnaturally repetitive stimuli. In this study, we investigated f0 processing of meaningful continuous speech. EEG responses evoked by stories in quiet were analysed with a novel method based on linear modelling that characterizes the neural tracking of the f0. We studied both the strength and the spatio-temporal properties of the f0-tracking response. Moreover, different samples of continuous speech (six stories by four speakers: two male and two female) were used to investigate the effect of voice characteristics on the f0 response.

The results indicated that response strength is inversely related to f0 frequency and rate of f0 change throughout the story. As a result, the male-narrated stories in this study (low and steady f0) evoked stronger f0-tracking compared to female-narrated stories (high and variable f0), for which many responses were not significant. The spatio-temporal analysis revealed that f0-tracking response generators were not fixed in the brainstem but were voice-dependent as well. Voices with high and variable f0 evoked subcortically-dominated responses with a latency between 7 and 12 ms. Voices with low and steady f0 evoked responses that are both subcortically (latency of 13-15 ms) and cortically (latency of 23-26 ms) generated, with the right primary auditory cortex as a likely cortical source. Finally, additional experiments revealed that response strength greatly improves for voices with strong higher harmonics, which is particularly useful to boost the small responses evoked by voices with high f0.


title: Integrated Collection of Stem Cell Bank data, a data portal for standardized stem cell information

abstract: The last decade has witnessed an extremely rapid increase in the number of newly established stem cell lines. However, due to the lack of a standardized format, data exchange among stem cell line resources has been challenging, and no system can search all stem cell lines across resources worldwide. To solve this problem, we have developed Integrated Collection of Stem Cell Bank data (ICSCB) (http://icscb.stemcellinformatics.org/), the largest database search portal for stem cell line information, based on the standardized data items and terms of the MIACARM framework. Currently, ICSCB can retrieve >16,000 cell lines from four major data resources in Europe, Japan, and the United States. ICSCB is automatically updated to provide the latest cell line information, and its integrative search helps users collect cell line information for over 1,000 diseases including many rare diseases worldwide, which has been a formidable task, thereby distinguishing itself from other database search portals.


title: Autophagy is required for self-incompatible pollen rejection in two transgenic Arabidopsis thaliana accessions

abstract:
Successful reproduction in the Brassicaceae is mediated by a complex series of interactions between the pollen and the pistil, and some species have an additional layer of regulation with the self-incompatibility trait. While the initial activation of the self-incompatibility pathway by the pollen S-locus protein11/S-locus cysteine-rich peptide and the stigma S Receptor Kinase is well characterized, the downstream mechanisms causing self-pollen rejection are still not fully understood. In previous studies, we had detected the presence of autophagic bodies with self-incompatible pollinations in Arabidopsis lyrata and transgenic A. thaliana lines, but it was not known if autophagy was essential for self-pollen rejection. Here, we investigated the requirement of autophagy in this response by crossing mutations in the essential AUTOPHAGY7 (ATG7) or AUTOPHAGY5 (ATG5) genes into two different transgenic self-incompatible A. thaliana lines in the Col-0 and C24 accessions. By using these previously characterized transgenic lines that express A. lyrata and A. halleri self-incompatibility genes, we demonstrated that disrupting autophagy can weaken their self-incompatible responses in the stigma. When the atg7 or atg5 mutations were present, an increased number of self-incompatible pollen were found to hydrate and form pollen tubes that successfully fertilized the self-incompatible pistils. Additionally, we confirmed the presence of GFP-ATG8a labelled autophagosomes in the stigmatic papillae following self-incompatible pollinations. Together, these findings support the requirement of autophagy in the self-incompatibility response and add to the growing understanding of the cellular events that take place in the stigma to reject self-pollen.

One Sentence SummaryIn self-incompatible transgenic Arabidopsis thaliana lines, autophagy is an integral part of the cellular responses in the stigma to efficiently block fertilization by self-incompatible pollen.

category: plant biology


title: Temporal uncertainty enhances suppression of neural responses to predictable visual stimuli

abstract: Predictive processing has been proposed as a fundamental cognitive mechanism to account for how the brain interacts with the external environment via its sensory systems. In vision, contextual information triggers predictions about the content ("what") of environmental stimuli to update an internal generative model of the surrounding world. However, visual information dynamically changes across time, and temporal predictability ("when") may influence the impact of internal predictions on visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information ("what") is affected by temporal predictability ("when"). In line with previous findings, we observed suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early visual responses, with the feature specificity of early visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable visual stimuli. These findings converge to suggest that the cognitive system processes visual features of temporally predictable stimuli in higher detail, while processing temporally uncertain stimuli may rely more heavily on abstract internal expectations.


title: The importance of animal weapons and fighting style in animal contests

abstract: In many species that fight over resources, individuals use specialized structures to gain mechanical advantage over their rivals during contests (i.e., weapons). Although weapons are widespread across animals, how they affect the probability of winning contests is still debated. According to theory, understanding the weapons function in contests depends on identifying differences in how weapons are measured (e.g., weapon length versus shape), and in how weapons are used during fights. Here, we developed a meta-analysis spanning 1,138 studies, from which were drawn 52 species and 107 effect sizes to identify: (1) what aspects of animal weapons are measured in the literature, and how these measures bias our knowledge; (2) how animals use their weapons during fights - i.e., weapon function; and (3) if weapon function correlates to the magnitude of how weapons influence contest resolution. First, we found that most of the literature focuses on linear measures of weapons, such as length. The few reports on weapon performance (e.g., biting force) were found only for Crustacea and Squamata. This bias highlights that measuring performance of weapons such as horns and spines might increase the breadth of our knowledge on weapons. Furthermore, we also found that linear measures showed stronger effects on contest success than performance measures. Second, we divided weapon function into displays and fighting style (i.e., how the weapon is used during fights). Regarding displays, most species displayed their weapons before contests (59.61%), rather than the body (34.61%). A minority (three species, 5.76%) engaged in fights without any type of display. Thus, species that bear weapons almost always perform displays before engaging in physical contact, a common hypothesis in contest theory that was never tested across taxa until now. Regarding fighting style, we found that most weapons were used for more than one behaviour during fights (e.g., squeezing and pushing). Further, pushing seems to be the most common behaviour among species, but it is usually accompanied by another behaviour, such as lifting or squeezing. Thus, oversimplifying fighting style can bias results because some styles might impose contrasting biomechanical pressures (e.g., pushing vs squeezing). Third, we found that display type did not influence the importance of weapon size on contests. Fighting style, on the other hand, influenced the effect of weapon size on contest outcome significantly. Species that used their weapons to impact, pierce or squeeze showed smaller differences between winners and losers when compared to pushing or lifting (and multifunctional weapons). Thus, pushing and lifting seem important for selecting larger weapons - even though some of them might also be used for squeezing, piercing or impacting. Overall, our results show that we have a biased understanding of animal weapons, built mostly on weapon size alone. Further, our analyses show that the importance of weapon size differs depending on the fighting style. If we lessen those biases, we will have a better and broader understanding of how weapons evolve and diversify.


title: Covering soybean leaves with cellulose nanofiber changes leaf surface hydrophobicity and confers resistance against Phakopsora pachyrhizi

abstract: Asian soybean rust (ASR) caused by Phakopsora pachyrhizi, an obligate biotrophic fungal pathogen, is the most devastating soybean production disease worldwide. Currently, timely fungicide application is the only means to control ASR in the field. We investigated cellulose nanofiber (CNF) application on ASR disease management. CNF-treated leaves showed reduced lesion number after P. pachyrhizi inoculation compared to control leaves, indicating that covering soybean leaves with CNF confers P. pachyrhizi resistance. We also demonstrated that formation of P. pachyrhizi pre-infection structures including germ-tubes and appressoria, and also gene expression related to these formations, such as chitin synthases (CHSs), were significantly suppressed in CNF-treated soybean leaves compared to control leaves. Moreover, contact angle measurement revealed that CNF converts soybean leaf surface properties from hydrophobic to hydrophilic. These results suggest that CNF can change soybean leaf surface hydrophobicity, conferring resistance against P. pachyrhizi, based on the reduced expression of CHSs, as well as reduced formation of pre-infection structures. This is the first study to investigate CNF application to control field disease.


title: Cell growth model with stochastic gene expression helps understand the growth advantage of metabolic exchange and auxotrophy

abstract:
During cooperative growth, microbes often experience higher fitness, due to sharing of resources by metabolic exchange and herd protection through biofilm structures. However, the trajectory of evolution of competitive species towards cooperation is not known. Moreover, existing models (based on optimisation of steady-state resources or fluxes) are often unable to explain the growth advantage for the cooperating species, even for simple reciprocally cross-feeding auxotrophic pairs. We present an abstracted model of cell growth that considers the stochastic burst-like gene expression of biosynthetic pathways of limiting biomass precursor metabolites, and directly connects their cellular levels to growth and division using a "metabolic sizer/adder" rule. Our model recapitulates Monods law and yields the experimentally observed right-skewed long-tailed distribution of cell doubling times. The model further predicts the growth effect of secretion and uptake of metabolites, by linking it to changes in the internal metabolite levels. The model also explains why auxotrophs may grow faster when provided the metabolite they cannot produce, and why a pair of reciprocally cross-feeding auxotrophs can grow faster than prototrophs. Overall, our framework allows us to predict the growth effect of metabolic interactions in microbial communities and also sets the stage to study the evolution of these interactions.

ImportanceCooperative behaviours are highly prevalent in the wild, but we do not understand how it evolves. Metabolic flux models can demonstrate the viability of metabolic exchange as cooperative interactions, but steady-state growth models cannot explain why cooperators grow faster. We present a stochastic model that connects growth to the cells internal metabolite levels and quantifies the growth effect of metabolite exchange and auxotrophy. We show that a reduction in gene expression noise explains why cells that import metabolites or become auxotrophs can grow faster, and also why reciprocal cross-feeding of metabolites between complementary auxotrophs allow them to grow faster. Our framework can simulate the growth of interacting cells, which will enable us to understand the possible trajectories of the evolution of cooperation in silico.

category: systems biology


title: Deep learning to decipher the progression and morphology of axonal degeneration

abstract:
BackgroundAxonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and to develop effective therapeutic interventions. Here, we evaluated the progression of AxD in cortical neurons using a novel microfluidic device in combination with a deep learning tool, the EntireAxon, that we developed for the enhanced-throughput analysis of AxD on microscopic images.

ResultsThe EntireAxon convolutional neural network sensitively and specifically segmented the features of AxD, including axons, axonal swellings, and axonal fragments, and its performance exceeded that of human expert raters. In an in vitro model of AxD in hemorrhagic stroke induced by the hemolysis product hemin, we detected the concentration- and time-dependent degeneration of axons leading to a decrease in axon area, while the axonal swelling and axonal fragment area increased. Time course analysis revealed that axonal swellings preceded axon fragmentation, suggesting that swellings may be reliable predictors of AxD. Using a recurrent neural network, we further identified four morphological patterns of AxD (granular, retraction, swelling, and transport degeneration) in cortical axons subjected to hemin.

ConclusionsThese findings indicate a morphological heterogeneity of AxD under pathophysiologic conditions. The combination of the microfluidic device with the EntireAxon deep learning tool enable the systematic analysis of AxD but also unravel a so far unknown intricacy in which AxD can occur in a disease context.


title: FAM13A regulates KLRG1 expression and interferon gamma production of natural killer cells

abstract: The polymorphism of the gene FAM13A (family with sequence similarity 13, member A) is strongly linked to the risk of lung cancer and chronic obstructive pulmonary disease, which are among the leading causes of mortality and morbidity in lung-related diseases worldwide. However, the underlying molecular and cellular mechanisms through which FAM13A contributes to the pathogenesis of these diseases largely remain unclear. Here, using a Fam13a knock out (KO) mouse model, we showed that Fam13a depletion upregulated the expression of the terminal differentiation and inhibitory marker, KLRG1 (killer cell lectin-like receptor G1) in natural killer (NK) cells. NK cells from Fam13a-deficient mice showed impaired IFN-{gamma} production either against target tumor cells or following various cytokine cocktail stimulations. Furthermore, the number of lung metastases induced by B16F10 melanoma cells was increased in Fam13a-KO mice. Collectively, our data suggest a key role of FAM13A in regulating NK cell functions, indicating that the key lung-disease risk gene FAM13A might contribute to the pathogenesis of several lung diseases via regulating NK cells.


title: Histone demethylome map reveals combinatorial gene regulatory functions in embryonic stem cells

abstract: Epigenetic regulators and transcription factors establish distinct regulatory networks for gene regulation to maintain the embryonic stem cell (ESC) state. Although much has been learned regarding individual epigenetic regulators, their combinatorial functions remain elusive. Here, we report previously unknown combinatorial functions of histone demethylases (HDMs) in gene regulation of mouse ESCs. Generation of a histone demethylome (HDMome) map of 20 well-characterized HDMs based on their genome-wide binding revealed co-occupancy of HDMs in different combinations: KDM1A-KDM4B-KDM6A and JARID2-KDM2B-KDM4A-KDM4C-KDM5B largely co-occupy at enhancers and promoters, respectively. Mechanistic studies uncover that KDM1A-KDM6A combinatorially modulates P300/H3K27ac, H3K4me2 deposition and OCT4 recruitment that directs the OCT4/CORE regulatory network for target gene expression; while co-operative actions of JARID2-KDM2B-KDM4A-KDM4C-KDM5B control H2AK119ub1 and bivalent marks of polycomb-repressive complexes that facilitate the PRC regulatory network for target gene repression. Thus, combinatorial functions of HDMs differentially impact gene expression programs in mESCs.

category: genomics


title: Heterochromatin-dependent transcription of satellite DNAs in the Drosophila melanogaster female germline

abstract: Large blocks of tandemly repeated DNAs--satellite DNAs (satDNAs)--play important roles in heterochromatin formation and chromosome segregation. We know little about how satDNAs are regulated, however their misregulation is associated with genomic instability and human diseases. We use the Drosophila melanogaster germline as a model to study the regulation of satDNA transcription and chromatin. Here we show that complex satDNAs (>100-bp repeat units) are transcribed into long noncoding RNAs and processed into piRNAs (PIWI interacting RNAs). This satDNA piRNA production depends on the Rhino-Deadlock-Cutoff complex and the transcription factor Moonshiner--a previously-described non-canonical pathway that licenses heterochromatin-dependent transcription of dual-strand piRNA clusters. We show that this pathway is important for establishing heterochromatin at satDNAs. Therefore, satDNAs are regulated by piRNAs originating from their own genomic loci. This novel mechanism of satDNA regulation provides insight into the role of piRNA pathways in heterochromatin formation and genome stability.


title: Climate change and chill accumulation: implications for tree fruit production in cold winter regions

abstract: Winter chill accumulation is critical for the productivity and profitability of perennial tree fruit systems. Several studies have quantified the impacts of global warming on chill accumulation in the warmer production regions of the world, where insufficient chill events occur and their frequency is increasing. In contrast, we focus on a region with relatively cold winters-the Pacific Northwest United States (PNW)-where insufficient chill events are currently absent, and quantify the potential for introduction of these risks under climate change. Results identified spatial variation within the PNW, with chill accumulation projected to increase in some areas but decrease in others. There was also spatiotemporal variation in the driving factors of changes to chill accumulation. Even with decreases in chill accumulations, there are likely minimal issues with insufficient chill accumulation. However, delayed chill accumulation in combination with advances in the onset of heat accumulation can potentially shift the region from one where spring phenology is primarily forcing-driven to one where the dynamic interplay between chilling and forcing processes become important. These interactions might create production risks for varieties with high chill requirements, post mid-21st-century under high emissions scenarios. Future work should focus on understanding, modeling, and projecting responses across these overlapping chilling and forcing processes. Additionally, given significant spatial differences across a relatively small geographic range, it is also critical to understand and model these dynamics at a local landscape resolution for regions such as the PNW.


title: Climate change and chill accumulation: implications for tree fruit production in cold-winter regions


title: Aberrant DJ-1 expression underlies L-type calcium channel hypoactivity in tuberous sclerosis complex and Alzheimer's disease

abstract:
L-type voltage-dependent Ca2+ channels (L-VDCC) integrate synaptic signals to facilitate a plethora of cellular mechanisms. L-VDCC dysfunction is implicated in several neurological and psychiatric diseases. Despite their importance, signals upstream of L-VDCC activity that regulate their channel density, however, are poorly defined. In disease models with overactive mammalian target of rapamycin complex 1 (mTORC1) signaling (or mTORopathies), including tuberous sclerosis (TS) and Alzheimers disease (AD), we report a novel mechanism downstream of mTORC1 signaling that results in a deficit in dendritic L-VDCC activity. Deficits in L-VDCC activity are associated with increased expression of the mTORC1-regulated RNA-binding protein DJ-1. DJ-1 binds the mRNA coding the auxiliary Ca2+ channel subunit 2{delta}2 responsible for shuttling L-VDCC to the membrane and represses its expression. Moreover, this novel DJ-1/2{delta}2/L-VDCC pathway is disrupted in human AD and preclinical models of AD and TS. Our discovery that DJ-1 directs L-VDCC activity and L-VDCC-associated protein 2{delta}2 at the synapse suggests that DJ-1/2{delta}2/L-VDCC is a common, fundamental pathway disrupted in TS and AD that can be targeted in clinical mTORopathies.

Significance StatementMany neurological disorders share symptoms, despite disparity among diseases. Treatments are prescribed based on diagnosis rather than individual symptoms. While only treating symptoms may obscure the disease, mechanism-based drug development allows the two approaches to converge. Hub proteins, those that coordinate the expression of proteins that mediate specific cellular functions, may be dysregulated across a broad range of disorders. Herein, we show that the RNA-binding protein DJ-1 controls the activity of L-type voltage-dependent calcium channels (L-VDCC), via the expression of its auxiliary subunit alpha2delta2 (2{delta}2). Importantly, we demonstrate that this novel DJ-1/2{delta}2/L-VDCC pathway is commonly disrupted among neurological disorders, namely Alzheimers disease (AD) and Tuberous Sclerosis (TS). Collectively, these data rationalize mechanism-based drug therapy to treat disease.


title: Rethinking Remdesivir: Synthesis, Antiviral Activity and Pharmacokinetics of Oral Lipid Prodrugs

abstract: Remdesivir (RDV, GS-5734) is currently the only FDA-approved antiviral drug for the treatment of SARS CoV-2 infection. The drug is approved for use in adults or children 12-years or older who are hospitalized for the treatment of COVID-19 on the basis of an acceleration of clinical recovery for inpatients with this disease. Unfortunately, the drug must be administered intravenously, restricting its use to those requiring hospitalization for relatively advanced disease. RDV is also unstable in plasma and has a complex activation pathway which may contribute to its highly variable antiviral efficacy in SARS-CoV-2 infected cells. Potent orally bioavailable antiviral drugs for early treatment of SARS-CoV-2 infection are urgently needed and several including molnupiravir and PF-07321332 are currently in clinical development. We focused on making simple, orally bioavailable lipid analogs of Remdesivir nucleoside (RVn, GS-441524) that are processed to RVn-monophosphate, the precursor of the active RVn-triphosphate, by a single-step intracellular cleavage. In addition to high oral bioavailability, stability in plasma and simpler metabolic activation, new oral lipid prodrugs of RVn had submicromolar anti-SARS-CoV-2 activity in a variety of cell types including Vero E6, Calu-3, Caco-2, human pluripotent stem cell (PSC)-derived lung cells and Huh7.5 cells. In Syrian hamsters oral treatment with ODBG-P-RVn was well tolerated and achieved therapeutic levels in plasma above the EC90 for SARS-CoV-2. The results suggest further evaluation as an early oral treatment for SARS-CoV-2 infection to minimize severe disease and reduce hospitalizations.


title: Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli

abstract: Antibiotic treatment kills a large portion of a population, while a small, tolerant subpopulation survives. Tolerant bacteria disrupt antibiotic efficacy and increase the likelihood that a population gains antibiotic resistance, a growing health concern. We examined how E. coli transcriptional networks changed in response to lethal ampicillin concentrations. We are the first to apply transcriptional regulatory network (TRN) analysis to antibiotic tolerance by leveraging existing knowledge and our transcriptional data. TRN analysis shows that gene expression changes specific to ampicillin treatment are likely caused by specific sigma and transcription factors typically regulated by proteolysis. These results demonstrate that to survive lethal concentration of ampicillin specific regulatory proteins change activity and cause a coordinated transcriptional response that leverages multiple gene systems.


title: A lexical approach for identifying behavioral action sequences

abstract: Animals display characteristic behavioral patterns when performing a task, such as the spiraling of a soaring bird or the surge-and-cast of a male moth searching for a female. Identifying such recurring sequences occurring rarely in noisy behavioral data is key to understanding the behavioral response to a distributed stimulus in unrestrained animals. Existing models seek to describe the dynamics of behavior or segment individual locomotor episodes rather than to identify the rare and transient sequences of locomotor episodes that make up the behavioral response. To fill this gap, we develop a lexical, hierarchical model of behavior. We designed an unsupervised algorithm called "BASS" to efficiently identify and segment recurring behavioral action sequences transiently occurring in long behavioral recordings. When applied to navigating larval zebrafish, BASS extracts a dictionary of remarkably long, non-Markovian sequences consisting of repeats and mixtures of slow forward and turn bouts. Applied to a novel chemotaxis assay, BASS uncovers chemotactic strategies deployed by zebrafish to avoid aversive cues consisting of sequences of fast large-angle turns and burst swims. In a simulated dataset of soaring gliders climbing thermals, BASS finds the spiraling patterns characteristic of soaring behavior. In both cases, BASS succeeds in identifying rare action sequences in the behavior deployed by freely moving animals. BASS can be easily incorporated into the pipelines of existing behavioral analyses across diverse species, and even more broadly used as a generic algorithm for pattern recognition in low-dimensional sequential data.

category: animal behavior and cognition


title: A dissemination-prone morphotype enhances extrapulmonary organ entry by the fungus Cryptococcus neoformans

abstract: Environmental pathogens, which move from ecological niches to mammalian hosts, must adapt to dramatically different environments. Microbes that disseminate farther, including the fungal meningitis pathogen Cryptococcus neoformans, require additional adaptation to diverse tissues. When C. neoformans enters the lungs, infecting cells (<10 m diameter) enlarge (>30 m diameter), then form a heterogeneous population. The brain contains uniformly small cells ([~]7 m). We demonstrate that formation of a small C. neoformans morphotype - called "seed" cells due to their disseminating ability - is critical for extrapulmonary organ entry. Seed cell formation is triggered by environmental factors, including C. neoformans environmental niche, pigeon guano. The underlying trigger, phosphate, can be released by tissue damage, potentially establishing a feed-forward loop of seed cell formation and dissemination. We demonstrate that C. neoformans size variation is not just a continuum but inducible subpopulations that change host interactions to facilitate microbe survival and spread.


title: First isolation and genetic characterization of Puumala orthohantavirus strains from France

abstract: Puumala orthohantavirus (PUUV) causes a mild form of haemorrhagic fever with renal syndrome (HFRS) called nephropathia epidemica (NE), regularly diagnosed in Europe. France represents the western frontier of the expansion of NE in Europe with two distinct areas: an endemic area (north-eastern France) where PUUV circulates in rodent populations, with detection of many human NE cases, and a non-endemic area (south-western France) where the virus is not detected, with only a few human cases being reported. France is thus a relevant country in which to study the factors that influence the evolution of PUUV distribution. In this study, we describe for the first time the isolation of two PUUV strains from two distinct French geographical areas: Ardennes (endemic area) and Loiret (non-endemic area). To isolate PUUV efficiently, we selected wild bank voles (Myodes glareolus, the specific reservoir of PUUV) captured in these areas and that were seronegative for anti-PUUV IgG (ELISA), but showed a non-negligible viral RNA load in their lung tissue (qRT-PCR). With this study design, we were able to cultivate and maintain these two strains in Vero E6 cells and also propagate both strains in immunologically neutral bank voles efficiently and rapidly. Complete coding sequences of the S and M segments were determined by Sanger sequencing from RNA extracted from positive bank voles (naturally and experimentally infected) and from supernatants of Vero E6 cell extracts. For the M segment, nucleotide sequences were 100% identical for both strains. For the S segment, the amino-acid sequences from each strain revealed one mismatch between sequences obtained from tissue and from cell supernatants, revealing distinct "bank vole" and a "cell" molecular profile. High-throughput sequencing confirmed Sanger results, and provided a better assessment of the impact of isolation methods on intra-host viral diversity.


title: Network Medicine Framework Shows Proximity of Polyphenol Targets and Disease Proteins is Predictive of the Therapeutic Effects of Polyphenols

abstract: Polyphenols, natural products present in plant-based foods, play a protective role against several complex diseases through their antioxidant activity and by diverse molecular mechanisms. Here we developed a network medicine framework to uncover the mechanistic roles of polyphenols on health by considering the molecular interactions between polyphenol protein targets and proteins associated with diseases. We find that the protein targets of polyphenols cluster in specific neighborhoods of the human interactome, whose network proximity to disease proteins is predictive of the molecules known therapeutic effects. The methodology recovers known associations, such as the effect of epigallocatechin 3-O-gallate on type 2 diabetes, and predicts that rosmarinic acid (RA) has a direct impact on platelet function, representing a novel mechanism through which it could affect cardiovascular health. We experimentally confirm that RA inhibits platelet aggregation and alpha granule secretion through inhibition of protein tyrosine phosphorylation, offering direct support for the predicted molecular mechanism. Our framework represents a starting point for mechanistic interpretation of the health effects underlying food-related compounds, allowing us to integrate into a predictive framework knowledge on food metabolism, bioavailability, and drug interaction.


title: A comparative analysis of SARS-CoV-2 antivirals in human airway models characterizes 3CLpro inhibitor PF-00835231 as a potential new treatment for COVID-19

abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of Coronavirus Disease 2019 (COVID-19). There is a dire need for novel effective antivirals to treat COVID-19, as the only approved direct-acting antiviral to date is remdesivir, targeting the viral polymerase complex. A potential alternate target in the viral life cycle is the main SARS-CoV-2 protease 3CLpro (Mpro). The drug candidate PF-00835231 is the active compound of the first anti-3CLpro regimen in clinical trials. Here, we perform a comparative analysis of PF-00835231, the pre-clinical 3CLpro inhibitor GC-376, and the polymerase inhibitor remdesivir, in alveolar basal epithelial cells modified to express ACE2 (A549+ACE2 cells). We find PF-00835231 with at least similar or higher potency than remdesivir or GC-376. A time-of-drug-addition approach delineates the timing of early SARS-CoV-2 life cycle steps in A549+ACE2 cells and validates PF-00835231s early time of action. In a model of the human polarized airway epithelium, both PF-00835231 and remdesivir potently inhibit SARS-CoV-2 at low micromolar concentrations. Finally, we show that the efflux transporter P-glycoprotein, which was previously suggested to diminish PF-00835231s efficacy based on experiments in monkey kidney Vero E6 cells, does not negatively impact PF-00835231 efficacy in either A549+ACE2 cells or human polarized airway epithelial cultures. Thus, our study provides in vitro evidence for the potential of PF-00835231 as an effective SARS-CoV-2 antiviral and addresses concerns that emerged based on prior studies in non-human in vitro models.

ImportanceThe arsenal of SARS-CoV-2 specific antiviral drugs is extremely limited. Only one direct-acting antiviral drug is currently approved, the viral polymerase inhibitor remdesivir, and it has limited efficacy. Thus, there is a substantial need to develop additional antiviral compounds with minimal side effects and alternate viral targets. One such alternate target is its main protease, 3CLpro (Mpro), an essential component of the SARS-CoV-2 life cycle processing the viral polyprotein into the components of the viral polymerase complex. In this study, we characterize a novel antiviral drug, PF-00835231, which is the active component of the first-in-class 3CLpro-targeting regimen in clinical trials. Using 3D in vitro models of the human airway epithelium, we demonstrate the antiviral potential of PF-00835231 for inhibition of SARS-CoV-2.


title: Tropism of SARS-CoV-2 in commonly used laboratory cell lines and their proteomic landscape during infection

abstract: The present pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is driving intense research activities to understand the basic biology of the virus and determine effective therapeutic strategies. The commonly used laboratory cell lines of human origin are the first line of experimental models to study the pathogenicity and performing antiviral assays. Thus, to find suitable cell models to study SARS-CoV-2, we assessed the tropism and cytopathogenicity of the first Swedish isolate of SARS-CoV-2 in six different cell lines of human origin and compared their growth characteristics to other globally isolated strains. Overall, Calu-3, Caco2, Huh7, and 293FT cell lines showed a high to moderate level of susceptibility to the majority of virus isolates. In Caco2 cells the virus can achieve high titers in the absence of any prominent cytopathic effect. The protein expression profile during SARS-CoV-2 infection revealed cell-type-specific regulation of cellular pathways. Type-I interferon signaling was identified as the common dysregulated cellular response in Caco2, Calu-3 and Huh7 cells. Overall, cell-type specific variability was noted for cytopathogenicity, susceptibility and cellular response to SARS-CoV-2. This study provides important clues regarding SARS-CoV-2 pathogenesis and can represent as a guide for future studies to design therapeutics.


title: Ion-water coupling controls class A GPCR signal transduction pathways

abstract: G-protein-coupled receptors (GPCRs) transmit signals across the cell membrane, forming the largest family of membrane proteins in humans. Most GPCRs activate through an evolutionarily conserved mechanism, which involves reorientation of helices and key residues, rearrangement of a hydrogen bonding network mediated by water molecules, and the expulsion of a sodium ion from a protonatable binding site. However, how these components interplay to engage the signal effector binding site remains elusive. Here, we applied information theory to molecular dynamics simulations of pharmaceutically important GPCRs to trace concerted conformational variations across the receptors. We discovered a conserved communication pathway that includes protein residues and cofactors and enables the exchange of information between the extracellular sodium binding site and the intracellular G-protein binding region, coupling the most highly conserved protonatable residues at long distance. Reorientation of internal water molecules was found to be essential for signal transmission along this pathway. By inhibiting protonation, sodium decoupled this connectivity, identifying the ion as a master switch that determines the receptors ability to move towards active conformations.


title: Genome-wide transcript and protein analysis reveals distinct features of aging in the mouse heart

abstract: Investigation of the molecular mechanisms of aging in the human heart is challenging due to confounding factors, such as diet and medications, as well limited access to tissues. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyzed transcriptome and proteome data from hearts of genetically diverse mice at ages 6, 12 and 18 months to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal distinct biological processes that are altered through the course of natural aging. Transcriptome analysis reveals a scenario of cardiac hypertrophy, fibrosis, and reemergence of fetal gene expression patterns. Proteome analysis reveals changes in energy metabolism and protein homeostasis. We found that for many protein complexes there is a decline in correlation between their component proteins with age, indicating age-related loss of stoichiometry. Some of the most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a viscious cycle of progressive breakdown in protein quality control with age. In addition, we identified genetic loci that modulate age-related changes in a variety of cellular processes, including protein degradation and sorting, suggesting that genetic variation can alter the rate of molecular aging.


title: Capturing non-local through-bond effects in molecular mechanics force fields I: Fragmenting molecules for quantum chemical torsion scans

abstract: Accurate molecular mechanics force fields for small molecules are essential for predicting protein-ligand binding affinities in drug discovery and understanding the biophysics of biomolecular systems. Torsion potentials derived from quantum chemical (QC) calculations are critical for determining the conformational distributions of small molecules, but are computationally expensive and scale poorly with molecular size. To reduce computational cost and avoid the complications of distal through-space intramolecular interactions, molecules are generally fragmented into smaller entities to carry out QC torsion scans. However, torsion potentials, particularly for conjugated bonds, can be strongly affected by through-bond chemistry distal to the torsion it-self. Poor fragmentation schemes have the potential to significantly disrupt electronic properties in the region around the torsion by removing important, distal chemistries, leading to poor representation of the parent molecules chemical environment and the resulting torsion energy profile. Here we show that a rapidly computable quantity, the fractional Wiberg bond order (WBO), is a sensitive reporter on whether the chemical environment around a torsion has been disrupted. We show that the WBO can be used as a surrogate to assess the robustness of fragmentation schemes and identify conjugated bond sets. We use this concept to construct a validation set by exhaustively fragmenting a set of druglike organic molecules and examine their corresponding WBO distributions derived from accessible conformations that can be used to evaluate fragmentation schemes. To illustrate the utility of the WBO in assessing fragmentation schemes that preserve the chemical environment, we propose a new fragmentation scheme that uses rapidly-computable AM1 WBOs, which are available essentially for free as part of standard AM1-BCC partial charge assignment. This approach can simultaneously maximize the chemical equivalency of the fragment and the substructure in the larger molecule while minimizing fragment size to accelerate QC torsion potential computation for small molecules and reducing undesired through-space steric interactions.


title: Structural Basis for Allosteric Control of the SERCA-Phospholamban Membrane Complex by Ca2+ and cAMP-dependent Phosphorylation

abstract: Phospholamban (PLN) is a mini-membrane protein that directly controls the cardiac Ca2+-transport response to {beta}-adrenergic stimulation, thus modulating cardiac output during the fight- or-flight response. In the sarcoplasmic reticulum membrane, PLN binds to the sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA), keeping this enzymes function within a narrow physiological window. PLN phosphorylation by cAMP-dependent protein kinase A or increase in Ca2+ concentration reverses the inhibitory effects through an unknown mechanism. Using oriented-sample solid-state NMR spectroscopy and replica-averaged NMR-restrained structural refinement, we reveal that phosphorylation of PLNs cytoplasmic regulatory domain signals the disruption of several inhibitory contacts at the transmembrane binding interface of the SERCA-PLN complex that are propagated to the enzymes active site, augmenting Ca2+ transport. Our findings address long-standing questions about SERCA regulation, epitomizing a signal transduction mechanism operated by posttranslationally-modified bitopic membrane proteins.


title: Neoplastic and Immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma.

abstract: Medulloblastoma (MB) is a heterogeneous disease in which neoplastic cells and associated immune cells contribute to disease progression. To better understand cellular heterogeneity in MB we use single-cell RNA sequencing, immunohistochemistry and deconvolution of transcriptomic data to profile neoplastic and immune populations in childhood MB samples. Neoplastic cells cluster primarily according to individual sample of origin which is in part due to the effect of chromosomal copy number gains and losses. Harmony alignment reveals novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes and are associated with clinical outcomes, including discrete photoreceptor-like cells in MB subgroups GP3 and GP4 and nodule-associated neuronally-differentiated cells in subgroup SHH. We definitively chart the spectrum of MB immune cell infiltrates, which include subgroup/subtype-associated developmentally-related neuron-pruning and antigen presenting myeloid cells. MB cellular diversity is recapitulated in genetically engineered mouse subgroup-specific models of MB. These findings provide a clearer understanding of both the neoplastic and immune cell heterogeneity in MB.


title: Size-independent mRNA synthesis and chromatin-based partitioning mechanisms generate and maintain constant amounts of protein per cell

abstract: Biosynthesis scales with cell size such that protein concentrations generally remain constant as cells grow. As an exception, synthesis of the cell-cycle inhibitor Whi5  sub-scales with cell size so that its concentration is lower in larger cells to promote cell-cycle entry. Here, we find that a transcriptional control uncouples Whi5 synthesis from cell size and, screening for similar genes, identify histones as the major class of sub-scaling transcripts besides WHI5. Histone synthesis is thereby matched to genome content rather than cell size. Such sub-scaling proteins are challenged by asymmetric cell division because proteins are typically partitioned in proportion to new-born cell volume. To avoid this fate, Whi5 uses chromatin-binding to partition similar protein amounts to each new-born cell regardless of cell size. Finally, disrupting both Whi5 synthesis and chromatin-based partitioning compromises G1 size control. Thus, specific transcriptional and partitioning mechanisms determine protein sub-scaling to control cell size.


title: Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer

abstract:
Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTPs), a sub-population of cancer cells that survive via reversible, non-genetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKIs) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome. Lentiviral barcoding/single cell RNA-sequencing reveal that HER2+ breast cancer cells cycle stochastically through a "pre-DTP" state, characterized by a G0-like expression signature and enriched for diapause and/or senescence genes. Trajectory analysis/cell sorting show that pre-DTPs preferentially yield DTPs upon HER2 TKI exposure. Cells with similar transcriptomes are present in HER2+ breast tumors and are associated with poor TKI response. Finally, biochemical experiments indicate that luminal-like DTPs survive via estrogen receptor-dependent induction of SGK3,leading to rewiring of the PI3K/AKT/mTORC1 pathway to enable AKT-independent mTORC1 activation.

STATEMENT OF SIGNIFICANCEDTPs are implicated in resistance to TKIs, other targeted therapies, and chemotherapy, but their ontogeny and vulnerabilities remain unclear. We find that HER2 TKI-DTPs emerge from stochastically arising primed cells ("pre-DTPs") that preferentially engage either of two distinct transcriptional programs upon TKI exposure. Our results provide new insights into DTP ontogeny and identify potential therapeutic vulnerabilities.


title: Targeting Oncogenic Src Homology 2 Domain-Containing Phosphatase 2 (SHP2) by Inhibiting its Protein-Protein Interactions

abstract: We developed a new class of inhibitors of protein-protein interactions of the SHP2 phosphatase, which is pivotal in multiple signaling pathways and a central target in the therapy of cancer and rare diseases. Currently available SHP2 inhibitors target the catalytic site or an allosteric pocket but lack specificity or are ineffective on disease-associated SHP2 mutants. Based on the consideration that pathogenic lesions cause signaling hyperactivation due to increased SHP2 association with cognate proteins, we developed peptide-based molecules with low nM affinity for the N-terminal Src homology domain of SHP2, good selectivity, stability to degradation and an affinity for pathogenic variants of SHP2 up to 20 times higher than for the wild-type protein. The best peptide reverted the effects of a pathogenic variant (D61G) in zebrafish embryos. Our results provide a novel route for SHP2-targeted therapies and a tool to investigate the role of protein-protein interactions in the function of SHP2.