title: Inferring a spatial code of cell-cell interactions across a whole animal body

abstract: Cell-cell interactions shape cellular function and ultimately organismal phenotype. However, the code embedded in the molecular interactions driving and sustaining the spatial organization of cells remains to be elucidated. Here we present a computational framework to infer the spatial code underlying cell-cell interactions from the transcriptomes of the cell types across the whole body of a multicellular organism. As core of this framework, we introduce our tool cell2cell, which uses the coexpression of ligand-receptor pairs to compute the potential for intercellular interactions, and we test it across the Caenorhabditis elegans body. Leveraging a 3D atlas of C. elegans cells, we also implement a genetic algorithm to identify the ligand-receptor pairs most informative of the spatial organization of cells. Validating the spatial code extracted with this strategy, the resulting intercellular distances are negatively correlated with the inferred cell-cell interactions. Furthermore, for selected cell-cell and ligand-receptor pairs, we experimentally confirm the communicatory behavior inferred with cell2cell and the genetic algorithm. Thus, our framework helps identify a code that predicts the spatial organization of cells across a whole-animal body.


title: Identification of new marker genes from plant single-cell RNA-seq data using interpretable machine learning methods

abstract:
An essential step in the analysis of single-cell RNA sequencing data is to classify specific cell types with marker genes. In this study, we have developed a machine learning pipeline called Single cell Predictive markers (SPmarker) to identify novel cell-type marker genes in the Arabidopsis root.

Unlike traditional approaches, our method uses interpretable machine learning methods to select marker genes. We have demonstrated that our method can (1) assign cell types based on cells that were labeled using published methods, (2) project cell types identified by trajectory analysis from one dataset to other datasets, and (3) assign cell types based on internal GFP markers.

Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, we have found more orthologous genes of these new marker genes in corresponding rice single cell clusters. We have also found 172 new marker genes for trichoblast in five non-Arabidopsis species, which expands number of marker genes for this cell type by 35-154%.

Our results represent a new approach to identify cell-type marker genes from scRNA-seq data and pave the way for cross-species mapping of scRNA-seq data in plants.

category: bioinformatics


title: ER bodies are induced by Pseudomonas syringae and negatively regulate immunity

abstract: ER bodies are endoplasmic reticulum-derived organelles present in plants belonging to the Brassicales order. In Arabidopsis thaliana, ER bodies are ubiquitous in cotyledons and roots, and present only in certain cell types in rosette leaves. However, both wounding and jasmonic acid treatment induce the formation of ER bodies in leaves. Formation of this structure is dependent on the transcription factor NAI1. The main components of the ER bodies are {beta}-glucosidases (BGLUs), enzymes that hydrolyze specialized compounds. In Arabidopsis, PYK10 (BGLU23) and BGLU18 are the most abundant ER body proteins. In this work, we found that ER bodies are downregulated as a consequence of the immune responses induced by bacterial flagellin perception. Arabidopsis mutants defective in ER body formation show enhanced responses upon flagellin perception and enhanced resistance to bacterial infections. Furthermore, the bacterial toxin coronatine induces the formation of de novo ER bodies in leaves and its virulence function is partially dependent on this structure. Finally, we show that performance of the polyphagous beet armyworm herbivore, Spodoptera exigua, increases in plants lacking ER bodies. Altogether, we provide new evidence for the role of the ER bodies in plant immune responses.

category: plant biology


title: Mosaic vaccination: how distributing different vaccines across a population could improve epidemic control

abstract: Although vaccination has been remarkably effective against some pathogens, for others, rapid antigenic evolution results in vaccination conferring only weak and/or short-lived protection. Consequently, considerable effort has been invested in developing more evolutionarily robust vaccines, either by targeting highly conserved components of the pathogen (universal vaccines) or by including multiple immunological targets within a single vaccine (multi-epitope vaccines). An unexplored third possibility is to vaccinate individuals with one of a number of qualitatively different vaccines, creating a  mosaic of individual immunity in the population. Here we explore whether a mosaic vaccination strategy can deliver superior epidemiological outcomes to  conventional vaccination, in which all individuals receive the same vaccine. We suppose vaccine doses can be distributed between distinct vaccine  targets (e.g., different surface proteins against which an immune response can be generated) and/or immunologically-distinct variants at these targets (e.g., strains); the pathogen can undergo antigenic evolution at both targets. Using simple mathematical models, we show that mosaic vaccination often outperforms conventional vaccination, leading to fewer infected individuals, improved vaccine efficacy, and lower individual risks over the course of the epidemic.

category: evolutionary biology


title: Modulation of implanted aortic scaffold- involvement of ECM and immune proteins

abstract:
Biological scaffold or implant is a popular choice for the preparation of tissue-engineered organs and has the potential to address donor shortage in the clinics. However, biological scaffolds prepared by physical or chemical agents cause damage to the extracellular matrix by potentially inducing immune responses after implantation. The current study explores an alternative route for the preparation of acellular scaffolds and explores the fate of the prepared scaffolds in a milieu of immune cells following implantation without using immunosuppressant. Using the syngeneic (Lewis male-Lewis female) and allogeneic (Brown Norway male-Lewis female) models and different tissue routes (subcutaneous vs omentum) for transplantation, normal blood vascular scaffolds were implanted which was converted to acellular vascular scaffolds by in vivo natural decellularization at the end of 2 months of observation. We also prepared chemically decellularized acellular scaffolds from normal untreated blood vascular scaffolds using a cocktail of chemicals which was also similarly placed in subcutaneous and omentum sites. Here, we applied in-depth quantitative proteomics along with histology and image analysis to comprehensively describe and compare the proteome of the natural and chemically decellularized scaffold. Our data confirm that site-specific advantages exist in modulating the ECM and regulating the immune responses (macrophage and T cells) following implantation, which possibly led to the production of an acellular scaffold (natural decellularization) under in vivo conditions. The current approach opens up the possibility to create tailor-made acellular scaffolds to build functional blood vessels. In addition, the identification of different tissue sites facilitates differential immune response against the scaffolds. This study provides a rich resource aimed toward an enhanced mechanistic understanding to study immune responses under similar settings in the field of transplantation and regenerative medicine.

Impact statementThe development of a scaffold helps in the preparation of a functional organ in the clinics. In the current study, we prepared an acellular vascular scaffold by utilizing site specific tissue changes and vis-a-vis compared with a conventionally chemically prepared biological scaffold at genomic and protein level, which helped us to identify immunological trigger following implantation. The current study which was carried out without any immunosuppressive agents could help to establish (a) alternative strategies for preparing biological scaffolds as well as (b) implantable sites as potential bioreactors to circumvent any adverse immune reactions for acceptance of the scaffold/implant post implantation.

category: bioengineering


title: Differential fate of acellular vascular scaffolds in vivo involves macrophages and T-cell subsets


title: A solution to temporal credit assignment using cell-type-specific modulatory signals

abstract: Animals learn and form memories by jointly adjusting the efficacy of their synapses. How they efficiently solve the underlying temporal credit assignment problem remains elusive. Here, we re-analyze the mathematical basis of gradient descent learning in recurrent spiking neural networks (RSNNs) in light of the recent single-cell transcriptomic evidence for cell-type-specific local neuropeptide signaling in the cortex. Our normative theory posits an important role for the notion of neuronal cell types and local diffusive communication by enabling biologically plausible and efficient weight update. While obeying fundamental biological constraints, including separating excitatory vs inhibitory cell types and observing connection sparsity, we trained RSNNs for temporal credit assignment tasks spanning seconds and observed that the inclusion of local modulatory signaling improved learning efficiency. Our learning rule puts forth a novel form of interaction between modulatory signals and synaptic transmission. Moreover, it suggests a computationally efficient learning method for bio-inspired artificial intelligence.

category: neuroscience


title: A representational similarity analysis of cognitive control during color-word Stroop

abstract:
Progress in understanding the neural bases of cognitive control has been supported by the paradigmatic color-word Stroop task, in which a target response (color name) must be selected over a more automatic, yet potentially incongruent, distractor response (word). For this paradigm, models have postulated complementary coding schemes: dorsomedial frontal cortex (DMFC) is proposed to evaluate the demand for control via incongruency-related coding, whereas dorsolateral prefrontal cortex (DLPFC) is proposed to implement control via goal and target-related coding. Yet, mapping these theorized schemes to measured neural activity within this task has been challenging. Here, we tested for these coding schemes relatively directly, by decomposing an event-related color-word Stroop task via representational similarity analysis (RSA). Three neural coding models were fit to the similarity structure of multi-voxel patterns of human fMRI activity, acquired from 65 healthy, young-adult males and females. Incongruency coding was predominant in DMFC, whereas both target and incongruency coding were present with indistinguishable strength in DLPFC. In contrast, distractor coding was strongly encoded within early visual cortex. Further, these coding schemes were differentially related to behavior: individuals with stronger DLPFC (and lateral posterior parietal cortex) target coding, but weaker DMFC incongruency coding, exhibited less behavioral Stroop interference. These results highlight the utility of the RSA framework for investigating neural mechanisms of cognitive control and point to several promising directions to extend the Stroop paradigm.

Significant StatementHow the human brain enables cognitive control -- the ability to override behavioral habits to pursue internal goals -- has been a major focus of neuroscience research. This ability has been frequently investigated by using the Stroop color-word naming task. With the Stroop as a test-bed, many theories have proposed specific neuroanatomical dissociations, in which medial and lateral frontal brain regions underlie cognitive control by encoding distinct types of information. Yet providing a direct confirmation of these claims has been challenging. Here, we demonstrate that representational similarity analysis (RSA), which estimates and models the similarity structure of brain activity patterns, can successfully establish the hypothesized functional dissociations within the Stroop task. RSA may provide a useful approach for investigating cognitive control mechanisms.


title: Low prevalence of natural Wolbachia in major malarial vectors Anopheles culicifacies s.l., and Anopheles stephensi: a first report

abstract: Wolbachia is an alpha-proteobacteria present in several arthropods. The present study focussed on the identification of Wolbachia in Anopheles culicifacies s.l., and Anopheles stephensi, which are wild malarial vector mosquitoes in India. A total of four hundred and eighty seven adult female mosquito samples were collected using taxonomic keys and confirmed by molecular analysis where 48.25% was Anopheles culicifacies s.l., and 51.75% was Anopheles stephensi. The presence of Wolbachia was identified using 16S rRNA, wsp and FtsZ genes, where nested PCR of 16S rRNA alone was successful and sequenced. Only seven mosquitoes (1.4%) were positive for Wolbachia. In silico and restriction digestion of 16S rRNA gene product using RsaI enzyme showed that the identified Wolbachia belongs to supergroup B, which is further supported by phylogenetic analysis. Low prevalence rate of natural Wolbachia was observed in An. culicifacies s.l. (1.7%) and An. stephensi (1.2%). This is the first report on the presence of Wolbachia in Anopheles culicifacies s.l. and Anopheles stephensi.

category: microbiology


title: EMBEDR: Distinguishing Signal from Noise in Single-Cell Omics Data

abstract: While single-cell "omics" based measurements hold the promise of unparalleled biological insight they remain a challenge to analyze owing to their high-dimensional nature. As a result, Dimensionality Reduction (DR) algorithms are necessary for data visualization and for downstream quantitative analysis. The lack of a principled methodology for separating signal from noise in DR algorithmic outputs has limited the confident application of these methods in unsupervised analyses of single-cell data, greatly hampering researchers ability to make data-driven discoveries. In this work we present an approach to quality assessment, EMBEDR, that works in conjunction with any DR algorithm to distinguish signal from noise in dimensionally-reduced representations of high-dimensional data. We apply EMBEDR to t-SNE- and UMAP-generated representations of published scRNA-seq data, revealing where lower-dimensional representations of the data are faithful renditions of biological signal in the data, and where they are more consistent with noise. EMBEDR produces easily interpreted p-values for each cell in a data set, facilitating the comparison of different DR methods and allowing optimization of their global hyperparameters. Most compellingly, EMBEDR allows for the analysis of single-cell data at a single-cell resolution, allowing DR methods to be used in a cell-wise optimal manner. Applying this technique to real data results in a biologically interpretable view of the data with no user supervision. We demonstrate the utility of EMBEDR in the context of several data sets and DR algorithms, illustrating its robustness and flexibility as well as its potential for making rigorous, quantitative analyses of single-cell omics data. EMBEDR is available as a Python package for immediate use.


title: Antagonistic modules, SIB1 and LSD1, regulate photosynthesis-associated nuclear genes via GOLDEN2-LIKE transcription factors in Arabidopsis

abstract: GOLDEN2-LIKE (GLK) transcription factors drive the expression of photosynthesis-associated nuclear genes (PhANGs), indispensable for chloroplast biogenesis. We previously demonstrated that the salicylic acid (SA)-induced SIGMA FACTOR-BINDING PROTEIN 1 (SIB1), a transcription coregulator and positive regulator of cell death, interacts with GLK1 and GLK2 to reinforce their activities. The SIB1-GLK interaction raises the level of light-harvesting antenna proteins in photosystem II, aggravating photoinhibition and singlet oxygen (1O2) burst. 1O2 then contributes to SA-induced cell death via EXECUTER 1 (EX1, 1O2 sensor protein)-mediated retrograde signaling upon reaching a critical level. We now reveal that LESION-SIMULATING DISEASE 1 (LSD1), a transcription coregulator and negative regulator of SA-primed cell death, interacts with GLK1/2 to repress their activities. Consistently, the overexpression of LSD1 represses GLK target genes including PhANGs, whereas the loss of LSD1 increases their expression. Remarkably, LSD1 overexpression inhibits chloroplast biogenesis, resembling the characteristic glk1glk2 double mutant phenotype. The subsequent chromatin immunoprecipitation analysis coupled with quantitative PCR further reveals that LSD1 inhibits the DNA-binding activity of GLK1 towards its target promoters. The SA-induced nuclear-targeted SIB1 appears to counteractively interact with GLK1/2, leading to the activation of EX1-mediated 1O2 signaling. Taken together, we provide a working model that SIB1 and LSD1, mutually exclusive SA-signaling components, antagonistically regulate GLK1/2 to fine-tune the expression of PhANGs, thereby modulating 1O2 homeostasis and related stress responses.


title: Diurnal transcript profiling of the diatom Seminavisrobusta reveals adaptations to a benthic lifestyle

abstract:
1Coastal regions contribute an estimated 20% of annual gross primary production in the oceans, despite occupying only 0.03% of their surface area. Diatoms frequently dominate coastal sediments, where they experience large variations in light regime resulting from the interplay of diurnal and tidal cycles. Here, we report on an extensive diurnal transcript profiling experiment of the motile benthic diatom Seminavis robusta. Nearly 90% (23,328) of expressed protein-coding genes and 66.9% (1124) of expressed long intergenic non-coding RNAs (lincRNAs) showed significant expression oscillations and are predominantly phasing at night with a periodicity of 24h. Phylostratigraphic analysis found that rhythmic genes are enriched in deeply conserved genes, while diatom-specific genes are predominantly associated with midnight expression. Integration of genetic and physiological cell cycle markers with silica depletion data revealed potential new silica cell wall associated gene families specific to diatoms. Additionally, we observed 1752 genes with a remarkable semidiurnal (12-h) periodicity, while the expansion of putative circadian transcription factors may reflect adaptations to cope with highly unpredictable external conditions. Taken together, our results provide new insights into the adaptations of diatoms to the benthic environment and serve as a valuable resource for diurnal regulation in photosynthetic eukaryotes.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

category: systems biology


title: Targeting aberrant dendritic integration to treat cognitive comorbidities of epilepsy

abstract:
Memory deficits are a debilitating symptom of epilepsy, but little is known about mechanisms underlying cognitive deficits. Here, we describe a Na+ channel-dependent mechanism underlying altered hippocampal dendritic integration, degraded place coding, and deficits in spatial memory.

Two-photon glutamate uncaging experiments revealed that the mechanisms constraining the generation of Na+ spikes in hippocampal 1st order pyramidal cell dendrites are profoundly degraded in experimental epilepsy. A selective Nav1.3 sodium channel blocker reversed this effect, and Nav1.3 channels were up-regulated selectively in principal neurons at the mRNA level. Finally, in-vivo two-photon imaging revealed that the Nav1.3 channel blocker improves degraded hippocampal spatial representations, and reverses hippocampal memory deficits.

Thus, a dendritic channelopathy may underlie cognitive deficits in epilepsy and targeting it pharmacologically may constitute a new avenue to enhance cognition.

One Sentence SummaryImpaired input computations via aberrant dendritic spikes in chronic epilepsy degrade neuronal place codes and spatial memory


title: Short linear motif based interactions and dynamics of the ezrin, radixin, moesin and merlin FERM domains

abstract: The ERM (ezrin, radixin and moesin) family of proteins and the related protein merlin participate in signaling events at the cell cortex. The proteins share an N-terminal FERM (band Four-point-one (4.1) ERM) domain comprised of three subdomains (F1, F2, and F3) that hold multiple binding sites for short linear peptide motifs. By screening the FERM domains of the ERMs and merlin against a phage library that display peptides representing the intrinsically disordered regions of the human proteome we identified more than 220 FERM binding peptides. The majority of the peptides contained an apparent Yx[FILV] motif, but ligands with alternative motifs were also found. Interactions with thirteen peptides were validated using a fluorescence polarization assay, and interactions with seven full-length proteins were validated through pull-down experiments. We investigated the energy landscapes of interactions between the moesin FERM domain and representative set of ligands using Rosetta FlexPepDock computational peptide docking protocols, which provide a detailed molecular understanding of the binding of peptides with distinct motifs (YxV and E[Y/F]xDFYDF) to different sites on the F3 subdomain. A third motif (FY[D/E]L(4-5x)PLxxx[L/V]) was proposed to bind more diffusely. By combining competition and modeling experiments, we further uncovered interdependencies between different types of ligands. The study expands the motif-based interactomes of the ERMs and merlin, and suggests that the FERM domain acts as a switchable interaction hub where one class of ligands to the F3 subdomain allosterically regulates binding of other F3 ligands.

category: biochemistry


title: MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data

abstract: A common approach to analyzing single-cell RNA-sequencing data is to cluster cells first and then identify differentially expressed genes based on the clustering result. However, clustering has an innate uncertainty and can be imperfect, undermining the reliability of differential expression analysis results. To overcome this challenge, we present MarcoPolo, a clustering-free approach to exploring differentially expressed genes. To find informative genes without clustering, MarcoPolo exploits the bimodality of gene expression to learn the group information of the cells with respect to the expression level directly from given data. Using simulations and real data analyses, we showed that our method puts biologically informative genes at high ranks more robustly than other existing methods. As our method provides information on how cells can be grouped for each gene, it can help identify cell types that are not separated well in the standard clustering process. Our method can also be used as a feature selection method to improve the robustness of the dimension reduction against changes in the parameters involved in the process.


title: A novel, ataxic mouse model of Ataxia Telangiectasia caused by a clinically relevant nonsense mutation

abstract: Ataxia Telangiectasia (A-T) and Ataxia with Ocular Apraxia Type 1 (AOA1) are devastating neurological disorders caused by null mutations in the genome stability genes, A-T mutated (ATM) and Aprataxin (APTX), respectively. Our mechanistic understanding and therapeutic repertoire for treating these disorders is severely lacking, in large part due to the failure of prior animal models with similar null mutations to recapitulate the characteristic loss of motor coordination (i.e., ataxia) and associated cerebellar defects. By increasing genotoxic stress through the insertion of null mutations in both the Atm (nonsense) and Aptx (knockout) genes in the same animal, we have generated a novel mouse model that for the first time develops a progressively severe ataxic phenotype associated with atrophy of the cerebellar molecular layer. We find biophysical properties of cerebellar Purkinje neurons are significantly perturbed (e.g., reduced membrane capacitance, lower action potential thresholds, etc.), while properties of synaptic inputs remain largely unchanged. These perturbations significantly alter Purkinje neuron neural activity, including a progressive reduction in spontaneous action potential firing frequency that correlates with both cerebellar atrophy and ataxia over the animals first year of life. Double mutant mice also exhibit a high predisposition to developing cancer (thymomas) and immune abnormalities (impaired early thymocyte development and T-cell maturation), symptoms characteristic of A-T. Lastly, by inserting a clinically relevant nonsense-type null mutation in Atm, we demonstrate that Small Molecule Read-Through (SMRT) compounds can restore ATM production, indicating their potential as a future A-T therapeutic.


title: The Drosophila Baramicin polypeptide gene protects against fungal infection

abstract: The fruit fly Drososphila melanogaster combats microbial infection by producing a battery of effector peptides that are secreted into the haemolymph. Technical difficulties prevented the investigation of these short effector genes until the recent advent of the CRISPR/CAS era. As a consequence, many putative immune effectors remain to be characterized and exactly how each of these effectors contributes to survival is not well characterized. Here we describe a novel Drosophila antifungal peptide gene that we name Baramicin A. We show that BaraA encodes a precursor protein cleaved into multiple peptides via furin cleavage sites. BaraA is strongly immune-induced in the fat body downstream of the Toll pathway, but also exhibits expression in the nervous system. Importantly, we show that flies lacking BaraA are viable but susceptible to the enomopathogenic fungus Beauveria bassiana. Consistent with BaraA being directly antimicrobial, overexpression of BaraA promotes resistance to fungi and the IM10-like peptides produced by BaraA synergistically inhibit growth of fungi in vitro when combined with a membrane-disrupting antifungal. Surprisingly, BaraA males but not females display an erect wing phenotype upon infection. Collectively, we identify a new antifungal immune effector downstream of Toll signalling, improving our knowledge of the Drosophila antimicrobial response.

category: immunology


title: Asymmetric requirement of Dpp/BMP morphogen dispersal in the Drosophila wing disc

abstract: How morphogen gradients control patterning and growth in developing tissues remains largely unknown due to lack of tools manipulating morphogen gradients. Here, we generate two membrane-tethered protein binders that manipulate different aspects of Decapentaplegic (Dpp), a morphogen required for overall patterning and growth of the Drosophila wing. "HA trap" is based on a single-chain variable fragment (scFv) against the HA tag that traps HA-Dpp to mainly block its dispersal, while "Dpp trap" is based on a Designed Ankyrin Repeat Protein (DARPin) against Dpp that traps Dpp to block both its dispersal and signaling. Using these tools, we found that, while posterior patterning and growth require Dpp dispersal, anterior patterning and growth largely proceed without Dpp dispersal. We show that dpp transcriptional refinement from an initially uniform to a localized expression and persistent signaling in transient dpp source cells render the anterior compartment robust against the absence of Dpp dispersal. Furthermore, despite a critical requirement of dpp for the overall wing growth, neither Dpp dispersal nor direct signaling is critical for lateral wing growth after wing pouch specification. These results challenge the long-standing dogma that Dpp dispersal is strictly required to control and coordinate overall wing patterning and growth.

category: developmental biology


title: SCReadCounts: Estimation of cell-level SNVs from scRNA-seq data

abstract: Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference. To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of celllevel allele expression of germline heterozygous SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel recurrent somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available (https://github.com/HorvathLab/NGS) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source.


title: Sex differences and similarities in the neuroimmune response to central administration of poly I:C

abstract:
BackgroundThe neuroimmune system is required for normal neural processes, including modulation of cognition, emotion, and adaptive behaviors. Aberrant neuroimmune activation is associated with dysregulation of memory and emotion, though the precise mechanisms at play are complex and highly context dependent. Sex differences neuroimmune activation and function further complicate our understanding of its roles in cognitive and affective regulation.

MethodsHere, we characterized the physiological sickness and inflammatory response of the hippocampus following intracerebroventricular (ICV) administration of a synthetic viral mimic, polyinosinic:polycytidylic acid (poly I:C), in both male and female C57Bl/6 mice.

ResultsWe observed that poly I:C induced weight loss, fever, and elevations of cytokine and chemokines in the hippocampus of both sexes. Specifically, we found transient increases in gene expression and protein levels of IL-1, IL-1{beta}, IL-4, IL-6, TNF, CCL2, and CXCL10, where males showed a greater magnitude of response compared with females. Only males showed increased IFN and IFN{gamma} in response to poly I:C, whereas both males and females exhibited elevations of IFN{beta}, demonstrating a specific sex difference in the anti-viral response in the hippocampus.

ConclusionOur data suggest that type I interferons are one potential node mediating sex-specific cytokine responses and neuroimmune effects on cognition. Together, these findings highlight the importance of using both males and females and analyzing a broad set of inflammatory markers in order to identify the precise, sex-specific roles for neuroimmune dysregulation in neurological diseases and disorders.


title: Universal constraints on protein evolution in the long-term evolution experiment with Escherichia coli

abstract:
Although it is well known that abundant proteins evolve slowly across the tree of life, there is little consensus for why this is true. Here, I report that abundant proteins evolve slowly in the hypermutator populations of Lenskis long-term evolution experiment with Escherichia coli (LTEE). Specifically, the density of all observed mutations per gene, as measured in metagenomic time series covering 60,000 generations of the LTEE, significantly anti-correlates with mRNA abundance, protein abundance, and degree of protein-protein interaction. The same pattern holds for nonsynonymous mutation density. However, synonymous mutation density, measured across the LTEE hypermutator populations, positively correlates with protein abundance. These results show that universal constraints on protein evolution are visible in data spanning three decades of experimental evolution. Therefore, it should be possible to design experiments to answer why abundant proteins evolve slowly.

Significance StatementA universal evolutionary pattern is that highly abundant and highly interacting proteins evolve slowly. This pattern was discovered in analyses that cover millions of years worth of sequence variation, so it is not clear how long it takes (decades, centuries, millennia) for such patterns to emerge. Here, I report that this universal evolutionary pattern emerges in metagenomic data that cover just 30 years of experimental evolution.


title: Metabolic differentiation of co-occurring Accumulibacter clades revealed through genome-resolved metatranscriptomics

abstract:
Natural microbial communities consist of closely related taxa that may exhibit phenotypic differences and inhabit distinct niches. However, connecting genetic diversity to ecological properties remains a challenge in microbial ecology due to the lack of pure cultures across the microbial tree of life.  Candidatus Accumulibacter phosphatis is a polyphosphate-accumulating organism that contributes to the Enhanced Biological Phosphorus Removal (EBPR) biotechnological process for removing excess phosphorus from wastewater and preventing eutrophication from downstream receiving waters. Distinct Accumulibacter clades often co-exist in full-scale wastewater treatment plants and lab-scale enrichment bioreactors, and have been hypothesized to inhabit distinct ecological niches. However, since individual strains of the Accumulibacter lineage have not been isolated in pure culture to date, these predictions have been made solely on genome-based comparisons and enrichments with varying strain composition. Here, we used genome-resolved metagenomics and metatranscriptomics to explore the activity of co-existing Accumulibacter strains in an engineered bioreactor environment. We obtained four high-quality genomes of Accumulibacter strains that were present in the bioreactor ecosystem, one of which is a completely contiguous draft genome scaffolded with long Nanopore reads. We identified core and accessory genes to investigate how gene expression patterns differed among the dominating strains. Using this approach, we were able to identify putative pathways and functions that may confer distinct functions to Accumulibacter strains and provide key functional insights into this biotechnologically significant microbial lineage.

IMPORTANCE Candidatus Accumulibacter phosphatis is a model polyphosphate accumulating organism that has been studied using genome-resolved metagenomics, metatranscriptomics, and metaproteomics to understand the EBPR process. Within the Accumulibacter lineage, several similar but diverging clades are defined by shared sequence identity of the polyphosphate kinase (ppk1) locus. These clades are predicted to have key functional differences in acetate uptake rates, phage defense mechanisms, and nitrogen cycling capabilities. However, such hypotheses have largely been made based on gene-content comparisons of sequenced Accumulibacter genomes, some of which were obtained from different systems. Here, we performed time-series genome-resolved metatranscriptomics to explore gene expression patterns of co-existing Accumulibacter clades in the same bioreactor ecosystem. Our work provides an approach for elucidating ecologically relevant functions based on gene expression patterns between closely related microbial populations.

category: genomics


title: The Selenoprotein P 3' untranslated region is an RNA binding protein platform that fine tunes selenocysteine incorporation

abstract: Selenoproteins contain the 21st amino acid, selenocysteine (Sec), which is incorporated at select UGA codons when a specialized hairpin sequence, the Sec insertion sequence (SECIS) element, is present in the 3 UTR. Aside from the SECIS, selenoprotein mRNA 3 UTRs are not conserved between different selenoproteins within a species. In contrast, the 3-UTR of a given selenoprotein is often conserved across species, which supports the hypothesis that cis-acting elements in the 3-UTR other than the SECIS exert post-transcriptional control on selenoprotein expression. In order to determine the function of one such SECIS context, we chose to focus on the plasma selenoprotein, SELENOP, which is required to maintain selenium homeostasis as a selenium transport protein that contains 10 Sec residues. It is unique in that its mRNA contains two SECIS elements in the context of a highly conserved 843-nucleotide 3 UTR. Here we have used RNA affinity chromatography and identified PTBP1 as the major RNA binding protein that specifically interacts with the sequence between the two SECIS elements. We then used CRISPR/Cas9 genome editing to delete two regions surrounding the first SECIS element. We found that these sequences are involved in regulating SELENOP mRNA and protein levels, which are inversely altered as a function of selenium concentrations.

category: molecular biology


title: Regulation of Dopamine D1 Receptor Signaling at the Golgi Apparatus by a Low Affinity Dopamine Transporter

abstract: Dopamine is the main catecholamine in the brain and the kidney, where it controls a number of physiological functions such as locomotion, cognition, emotion, endocrine regulation and renal function. As a membrane impermeant hormone and neurotransmitter, dopamine is thought to signal by binding and activating dopamine receptors, members of the G protein couple receptor (GPCR) family, only on the plasma membrane. Here, using novel nanobody-based biosensors, we demonstrate for the first time that the dopamine D1 receptor (D1DR), the primary mediator of dopaminergic signaling in the brain and kidney, not only functions on the plasma membrane but becomes activated at the Golgi apparatus in the presence of its ligand. We present evidence that activation of the Golgi pool of D1DR is dependent on Organic Cation Transporter 2 (OCT2), a dopamine transporter, providing an explanation for how the membrane impermeant dopamine accesses subcellular pools of D1DR. We further demonstrate that dopamine activates Golgi-D1DR in the striatal medium spiny neurons (MSN) and this activity depends on OCT2 function. We also introduce a new approach to selectively interrogate compartmentalized D1DR signaling by inhibiting Gs coupling, using a nanobody-based chemical recruitment system. Using this strategy, we show that Golgi-localized D1DRs regulate cAMP production and mediate local protein kinase A activation. Together, our data suggest that spatially compartmentalized signaling hubs are previously unappreciated regulatory aspects of D1DR signaling. Our data also provide further evidence for the role of transporters in regulating subcellular GPCR activity.

category: cell biology


title: The OCT2 Transporter Regulates Dopamine D1 Receptor Signaling at the GolgiApparatus


title: Peptide Ancestry Informative Markers in Uterine Neoplasms from Women of European, African and Asian Ancestry

abstract: Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with molecular disease pathogenesis. Nonsynonymous single nucleotide polymorphisms (SNPs) encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis shows that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R2=0.9905). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues resulted in the quantitation of 62 pAIMs that correlate with self-described race and genotype-confirmed patient ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. These efforts describe a generalized set of markers for proteoancestry assessment that will further support studies investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

category: cancer biology


title: Beyond fear centers: a distributed fMRI-based neuromarker for the subjective experience of fear

abstract: The specific neural systems underlying the subjective feeling of fear remain vigorously debated in affective neuroscience. Here, we combined functional MRI with machine learning to identify and evaluate a sensitive and generalizable neural signature predictive of the momentary self-reported subjective fear experience across discovery (n=67), validation (n=20) and generalization (n=31) cohorts. We systematically demonstrate that accurate fear prediction crucially requires distributed brain systems, with important contributions from cortical (e.g., prefrontal, midcingulate and insular cortices) and subcortical (e.g., thalamus, periaqueductal gray, basal forebrain and amygdala) regions. We further demonstrate that the neural representation of subjective fear is distinguishable from the representation of conditioned threat and general negative affect. Overall, our findings suggest that subjective fear, which exhibits distinct neural representation with some other aversive states, is encoded in distributed systems rather than isolated  fear centers. This signature provides a neuromarker for monitoring fear-related neuropathology and evaluating novel treatments targeting pathological fear.


title: Demogenomic modeling of the timing and the processesof early European farmers differentiation

abstract:
The precise genetic origins of the first Neolithic farming populations, as well as the processes and the timing of their differentiation, remain largely unknown. Based on demogenomic modeling of high-quality ancient genomes, we show that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Near Eastern population with a strongly bottlenecked Western hunter-gatherer population after the Last Glacial Maximum. Moreover, the population branch leading to the first farmers of Europe and Anatolia is characterized by a 2,500-year period of extreme genetic drift during its westward range expansion. Based on these findings, we derive a spatially explicit model of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.

One-Sentence SummaryEarly European farmers emerged from multiple post LGM mixtures and experienced extreme drift during their westward expansion.


title: Integrating long-range regulatory interactions to predict gene expression using graph convolutional networks

abstract: Long-range spatial interactions among genomic regions are critical for regulating gene expression, and their disruption has been associated with a host of diseases. However, when modeling the effects of regulatory factors, most deep learning models either neglect long-range interactions or fail to capture the inherent 3D structure of the underlying genomic organization. To address these limitations, we present GC-MERGE, a Graph Convolutional Model for Epigenetic Regulation of Gene Expression. Using a graph-based framework, the model incorporates important information about long-range interactions via a natural encoding of spatial interactions into the graph representation. It integrates measurements of both the spatial genomic organization and local regulatory factors, specifically histone modifications, to not only predict the expression of a given gene of interest but also quantify the importance of its regulatory factors. We apply GC-MERGE to datasets for three cell lines - GM12878 (lymphoblastoid), K562 (myelogenous leukemia), and HUVEC (human umbilical vein endothelial) - and demonstrate its state-of-the-art predictive performance. Crucially, we show that our model is interpretable in terms of the observed biological regulatory factors, high-lighting both the histone modifications and the interacting genomic regions contributing to a genes predicted expression. We provide model explanations for multiple exemplar genes and validate them with evidence from the literature. Our model presents a novel setup for predicting gene expression by integrating multimodal datasets in a graph convolutional framework. More importantly, it enables interpretation of the biological mechanisms driving the models predictions. Available at: https://github.com/rsinghlab/GC-MERGE.


title: Predicting perturbation effects from resting state activity using functional causal flow

abstract: A crucial challenge in targeted manipulation of neural activity is to identify perturbation sites whose stimulation exerts significant effects downstream (high efficacy), a procedure currently achieved by labor-intensive trial-and-error. Targeted perturbations will be greatly facilitated by understanding causal interactions within neural ensembles and predicting the efficacy of perturbation sites before intervention. Here, we addressed this issue by recording changes in the prefrontal ensemble spiking activity of alert monkeys in response to single-electrode microstimulation and during resting periods. By deploying a novel statistical method for inferring the ensembles functional causal flow (FCF), we were able to reliably predict the spatiotemporal effects of micros-timulations only based on the functional interactions inferred at rest. When validating FCF using ground truth data from models of cortical circuits, we found that FCF is robust to noise and can be inferred from brief recordings of even a small fraction of neurons in the circuit. A detailed comparison of FCF to Granger causality highlighted the advantages of our new method in predicting perturbation effects on empirical data. Our results provide the foundation for using targeted circuit manipulations to develop new brain-machine interfaces and ameliorate cognitive dysfunctions in the human brain.


title: Crystal Structure of a Retroviral Polyprotein:Prototype Foamy Virus Protease-Reverse Transcriptase (PR-RT)

abstract:
In most cases, proteolytic processing of the retroviral Pol portion of the Gag-Pol polyprotein precursor produces protease (PR), reverse transcriptase (RT), and integrase (IN). However, foamy viruses (FVs), express Pol separately from Gag and, when Pol is processed, only the IN domain is released. Here, we report a 2.9 [A] resolution crystal structure of the mature PR-RT from prototype FV (PFV) that carries out both proteolytic processing and reverse transcription. PFV PR-RT is monomeric and the architecture of PFV PR is similar to one of the subunits of HIV-1 PR, which is a dimer. There is a C-terminal extension of PFV PR (101-145) that consists of two helices which are adjacent to the base of the RT palm subdomain, and anchors PR to RT. The polymerase domain of PFV RT consists of fingers, palm, thumb, and connection subdomains whose spatial arrangements are similar to the p51 subunit of HIV-1 RT. The RNase H and polymerase domains of PFV RT are connected by flexible linkers. Significant spatial and conformational (sub)domain rearrangements are therefore required for nucleic acid binding. The structure of PFV PR-RT provides insights into the conformational maturation of retroviral Pol polyproteins.

IMPORTANCERetroviruses such as HIV and other human and animal pathogens have evolved to maximize the protein-coding capacity of their genomes. Retroviruses synthesize large polyprotein precursors that are subsequently cleaved to produce mature functional enzymes and structural proteins from the same mRNA template. These polyproteins play an important role in the viral life cycle. We report the monomeric structure of the prototype foamy virus protease-reverse transcriptase fusion (PR-RT) which serves as both a protease and reverse transcriptase. The monomeric PR domain is folded in a similar way as a single subunit of dimeric HIV-1 PR. PR is anchored close to the fingers subdomain of the RT by a long C-terminal extension (CTE) that folds into two helices that pack against the palm subdomain of the RT. The RT is folded similarly to the p51 subunit of HIV-1 RT with the RNase H subdomain packed against the thumb and opposite the connection and palm subdomains. This structure offers insight into the structural arrangement of the domains and subdomains of immature retroviral polyproteins and provides support for the concept of developing drugs that target interfaces between immature enzymes that are present only in retroviral polyprotein precursors.

category: biophysics


title: The Physcomitrium (Physcomitrella) patens PpKAI2L receptors for strigolactones and related compounds highlight MAX2 dependent and independent pathways

abstract: In flowering plants, the /{beta} hydrolase DWARF14 (D14) perceives strigolactone (SL) hormones and interacts with the F-box protein MORE AXILLARY GROWTH2 (MAX2) to regulate developmental processes. The key SL biosynthetic enzyme, CAROTENOID CLEAVAGE DEOXYGENASE8 (CCD8), is present in the moss Physcomitrium (Physcomitrella) patens, and PpCCD8-derived compounds regulate plant extension. Based on germination assays using seeds of the parasitic plant Phelipanche ramosa, we propose that these compounds are non-canonical SLs. Perception of PpCCD8-derived compounds does not require the PpMAX2 homolog. Candidate receptors are among the 13 PpKAI2LIKE-A to -L genes, homologous to the ancestral D14 paralog KARRIKIN INSENSITIVE2 (KAI2). In Arabidopsis, AtKAI2 is the receptor for a still elusive endogenous KAI2-Ligand (KL). We show that in P. patens, among SL analogs, the (+)-GR24 enantiomer is a good mimic for PpCCD8-derived compounds, while the effects of the (-)-GR24 enantiomer, a KL mimic in flowering plants, are opposite. Interaction and binding assays of seven PpKAI2L proteins using pure enantiomers pinpoint at stereoselectivity towards (-)-GR24 for the (A-E) clade. Enzyme assays highlight strong hydrolytic activity of the PpKAI2L-H protein. Moss mutants for all PpKAI2L gene subclades were obtained and tested for their response to both enantiomers. We show that PpKAI2L-A to -E genes are not involved in PpCCD8-derived compound perception, but act in a PpMAX2-dependant pathway. In contrast, mutations in PpKAI2L-G, and -J genes abolish the response to (+)-GR24, suggesting that encoded proteins are receptors for PpCCD8-derived SLs.


title: High-throughput characterization of 309 photocrosslinker-bearing ASIC1a variants maps residues critical for channel function and pharmacology

abstract: Incorporation of non-canonical amino acids (ncAAs) can endow proteins with novel functionalities, such as crosslinking or fluorescence. In ion channels, the function of these variants can be studied with great precision using standard electrophysiology, but this approach is typically labor intensive and low throughput. Here, we establish a high-throughput protocol to conduct functional and pharmacological investigations of ncAA-containing hASIC1a (human acid-sensing ion channel 1a) variants in transiently transfected mammalian cells. We introduce three different photocrosslinking ncAAs into 103 positions and assess the function of the resulting 309 variants with automated patch-clamp (APC). We demonstrate that the approach is efficient and versatile, as it is amenable to assessing even complex pharmacological modulation by peptides. The data show that the acidic pocket is a major determinant for current decay and live-cell crosslinking provides insight into the hASIC1a-psalmotoxin-1 interaction. Further, we provide evidence that the protocol can be applied to other ion channels, such as P2X2 and GluA2 receptors. We therefore anticipate the approach to enable future APC-based studies of ncAA-containing ion channels in mammalian cells.


title: High-throughput characterization of photocrosslinker-bearing ion channel variants to map residues critical for function and pharmacology


title: Memory Transfer of Random Time Patterns Across Modalities

abstract: Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, temporal patterns implicitly learned within one modality can also be recognised in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers (N=24, 12 females, 12 males) using electroencephalography (EEG), while participants were exposed to brief sequences of randomly-timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment, enabling implicit learning. Replicating previous behavioural findings, we showed that participants benefit from temporal information learned in audition, and that they can apply this information to stimuli presented in vision. Such memory transfer was not observed from vision to audition. However, using an analysis of EEG response learning curves, we showed that learning temporal structures both within and across modalities modulates single-trial EEG response amplitudes in both conditions (audition to vision and vision to audition). Interestingly, the neural correlates of temporal learning within modalities relied on modality-specific brain regions, while learning transfer affected activity in frontal regions, suggesting distinct mechanisms. The cross-modal effect could be linked to frontal beta-band activity. The neural effects of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. Thus, both modality-specific mechanisms for learning of temporal information, and general mechanisms which mediate learning transfer across modalities, have distinct physiological signatures that are observable in the EEG.


title: Initial ciliary assembly in Chlamydomonas requires Arp2/3 complex-dependent endocytosis

abstract: Ciliary assembly, trafficking, and regulation are dependent on microtubules, but the mechanisms of ciliary assembly also require the actin cytoskeleton. Here, we dissect subcellular roles of actin in ciliogenesis by focusing on actin networks nucleated by the Arp2/3 complex in the powerful ciliary model, Chlamydomonas. We find the Arp2/3 complex is required for the initial stages of ciliary assembly when protein and membrane are in high demand, but cannot yet be supplied from the Golgi complex. We provide evidence for Arp2/3 complex-dependent clathrin-mediated endocytosis of ciliary proteins, an increase in endocytic activity upon induction of ciliary growth, and relocalization of plasma membrane proteins to newly formed cilia. Our data support a new model of ciliary protein and membrane trafficking during early ciliogenesis whereby proteins previously targeted to the plasma membrane are reclaimed by Arp2/3 complex-dependent clathrin-mediated endocytosis for initial ciliary assembly.


title: Mapping Epigenetic Divergence in the Massive Radiation of Lake Malawi Cichlid Fishes

abstract: Epigenetic variation modulates gene expression and can be heritable. However, knowledge of the contribution of epigenetic divergence to adaptive diversification in nature remains limited. The massive evolutionary radiation of Lake Malawi cichlid fishes displaying extensive phenotypic diversity despite extremely low sequence divergence is an excellent system to study the epigenomic contribution to adaptation. Here, we present a comparative genome-wide methylome and transcriptome study, focussing on liver and muscle tissues in phenotypically divergent cichlid species. In both tissues we find substantial methylome divergence among species. Differentially methylated regions (DMR), enriched in evolutionary young transposons, are associated with transcription changes of ecologically-relevant genes related to energy expenditure and lipid metabolism, pointing to a link between dietary ecology and methylome divergence. Unexpectedly, half of all species-specific DMRs are shared across tissues and are enriched in developmental genes, likely reflecting distinct epigenetic developmental programmes. Our study reveals substantial methylome divergence in closely-related cichlid fishes and represents a resource to study the role of epigenetics in species diversification.


title: LinearTurboFold: Fast Folding and Alignment for RNA Homologs with Applications to Coronavirus

abstract:
The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes ([~]30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Folds purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 and 3 UTRs ([~]29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.

Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus ([~]30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics.


title: LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2


title: Fever temperatures impair hemolysis caused by strains of Escherichia coli and Staphylococcus aureus

abstract: Hemolysis modulates susceptibility to bacterial infections and predicts poor sepsis outcome. Hemolytic bacteria induce upon infection a reversible fever response from the host that may aid in pathogen clearance. To delineate the role of fever temperatures on the growth and infectivity of two hemolytic bacteria that are known to evoke fever in patients via hemotoxins, we used high-sensitivity microcalorimetry to measure the evolution of heat production by fever-inducing strains of Escherichia coli and Staphylococcus aureus under fever conditions. We determined specific aggregation profiles at temperatures equal to or exceeding 38.5{square}. We confirmed these results through bacterial incubation at relevant temperatures revealing the presence or absence of hemolysis. We thus reveal an additional positive role of febrile temperatures in directly contributing to the immune response, through the abolishment of hemolysis.


title: Snowball Earths, population bottlenecks, and the evolution of marine photosynthetic bacteria

abstract: Prochlorococcus are the most abundant photosynthetic organisms in the modern ocean. A massive DNA loss event occurred in their early evolutionary history, leading to highly reduced genomes in nearly all lineages, as well as enhanced efficiency in both nutrient uptake and light absorption. The environmental landscape that shaped this ancient genome reduction, however, remained unknown. Through careful molecular clock analyses, we established that this Prochlorococcus genome reduction occurred during the Neoproterozoic Snowball Earth climate catastrophe. The lethally low temperature and exceedingly dim light during the Snowball Earth event would have inhibited Prochlorococcus growth and proliferation and caused severe population bottlenecks. These bottlenecks are recorded as an excess of deleterious mutations that accumulated across genomic regions in the descendant lineages. Prochlorococcus adaptation to extreme environmental conditions during Snowball Earth intervals can be inferred by tracing the evolutionary paths of genes that encode key metabolic potential. This metabolic potential includes modified lipopolysaccharide structure, strengthened peptidoglycan biosynthesis, the replacement of a sophisticated circadian clock with an hourglass-like mechanism that resets daily for dim light adaption, and the adoption of ammonia diffusion as an efficient membrane transporter-independent mode of nitrogen acquisition. In this way, the Neoproterozoic Snowball Earth event altered the physiological characters of Prochlorococcus, shaping their ecologically vital role as the most abundant primary producers in the modern oceans.


title: Snowball Earths, population bottlenecks, and Prochlorococcus evolution


title: Time-resolved structured illumination microscopy reveals key principles of Xist RNA spreading

abstract:
Xist RNA directs the process of X-chromosome inactivation in mammals by spreading in cis along the chromosome from which it is transcribed and recruiting chromatin modifiers to silence gene transcription. To elucidate mechanisms of Xist RNA cis-confinement, we established a sequential dual color labeling, super-resolution imaging approach to trace individual Xist RNA molecules over time, enabling us to define fundamental parameters of spreading. We demonstrate a feedback mechanism linking Xist RNA synthesis and degradation, and an unexpected physical coupling between preceding and newly synthesized Xist RNA molecules. Additionally, we show that the protein SPEN, a key factor for Xist-mediated gene-silencing, has a distinct function in Xist RNA localization, stability and in coupling behavior. Our results provide important insights towards understanding the unique dynamic properties of Xist RNA.

One Sentence SummaryVisualizing Xist RNA dynamics in single cells during X chromosome inactivation


title: A mixed model approach for estimating drivers of microbiota community composition and differential taxonomic abundance

abstract:
O_LINext-generation sequencing (NGS) and meta-barcoding approaches have revolutionized understanding of within-host communities, such as the gut microbiome, in humans and laboratory animals. The application of such approaches in wild animal populations is growing, but there is a disconnect between the widely-applied generalised linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology which is typically applied to meta-barcoding data.
C_LIO_LIHere, we describe and illustrate a novel GLMM-based approach for analysing the taxon-specific sequence read counts derived from standard meta-barcoding data. This approach allows us to decompose the contribution of different drivers of variation in community structure (e.g. year, season, individual host), via interaction terms in the random effects structure of the model. We also show how these models can be used to determine the degree to which specific taxa or taxonomic groups are responsible for variance attributed to different drivers.
C_LIO_LITo illustrate this approach, we applied it to two cross-sectional meta-barcoding data sets from the Soay Sheep population of St. Kilda. The GLMM approach yielded results that were in agreement with more classical approaches from community ecology, showing that variation the gut microbiota community in these sheep was better explained by age group than by season. We were able to quantify the contributions of different sources of variation to community structure, and also to drill down into the model predictions to show that the age effects we observed were principally due to increases in taxa of the phyla Bacteroidetes and declines in taxa of the phyla Firmicutes.
C_LIO_LIOur proposed models offer a powerful new approach to understanding the drivers of variation in estimates of community structure derived from meta-barcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate that contribution of host genotype, environment, and microbial/parasite phylogeny to observed community structure, and thus provide a powerful means to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities.
C_LI


title: Ipomoeassin-F inhibits the in vitro biogenesis of the SARS-CoV-2 spike protein and its host cell membrane receptor

abstract: In order to produce proteins essential for their propagation, many pathogenic human viruses, including SARS-CoV-2 the causative agent of COVID-19 respiratory disease, commandeer host biosynthetic machineries and mechanisms. Three major structural proteins, the spike, envelope and membrane proteins, are amongst several SARS-CoV-2 components synthesised at the endoplasmic reticulum (ER) of infected human cells prior to the assembly of new viral particles. Hence, the inhibition of membrane protein synthesis at the ER is an attractive strategy for reducing the pathogenicity of SARS-CoV-2 and other obligate viral pathogens. Using an in vitro system, we demonstrate that the small molecule inhibitor ipomoeassin F (Ipom-F) potently blocks the Sec61-mediated ER membrane translocation/insertion of three therapeutic protein targets for SARS-CoV-2 infection; the viral spike and ORF8 proteins together with angiotensin-converting enzyme 2, the host cell plasma membrane receptor. Our findings highlight the potential for using ER protein translocation inhibitors such as Ipom-F as host-targeting, broad-spectrum, antiviral agents.


title: Emerging Concern of Scientific Fraud: Deep Learning and Image Manipulation

abstract: Scientific fraud by image duplications and manipulations within western blot images is a rising problem. Currently, problematic western blot images are mainly detected by checking repeated bands or through visual observation. However, the completeness of the above methods in detecting problematic images has not been demonstrated. Here we show that Generative Adversarial Nets (GANs) can generate realistic western blot images that indistinguishable from real western blots. The overall accuracy of researchers for identifying synthetic western blot images is 0.52, which almost equal to blind guess (0.5). We found that GANs can generate western blot images with bands of the expected lengths, widths, and angles in desired positions that can fool researchers. For the case study, we find that the accuracy of detecting the synthetic western blot images is related to years of researchers performed studies relevant to western blots, but there was no apparent difference in accuracy among researchers with different academic degrees. Our results demonstrate that GANs can generate fake western blot images to fool existing problematic image detection methods. Therefore, more information is needed to ensure that the western blots appearing in scientific articles are real. We argue to require every western blot image to be uploaded along with a unique identifier generated by the laboratory machine and to peer review these images along with the corresponding submitted articles, which may reduce the incidence of scientific fraud.

category: scientific communication and education


title: Disease specific alterations in the olfactory mucosa of patients with Alzheimer's disease

abstract: Olfactory dysfunction manifests early in several neurodegenerative disorders. Olfaction is orchestrated by olfactory mucosal cells located in the upper nasal cavity. However, it is unclear how this tissue reflects key neurodegenerative features in Alzheimers disease. Here we report that Alzheimers disease olfactory mucosal cells obtained from live individuals secrete toxic amyloid-beta. We detail cell-type-specific gene expression patterns, unveiling 147 differentially expressed disease-associated genes compared to the cognitively healthy controls, and 5 distinct populations in globose basal cell -, myofibroblast-, and fibroblast/ stromal - like cells in vitro. Overall, coordinated alteration of RNA and protein metabolism, inflammatory processes and signal transduction were observed in multiple cell populations, suggesting a key role in pathophysiology. Our results demonstrate the potential of olfactory cell cultures in modelling Alzheimers disease advocate their use for diagnostic purposes. Moreover, for the first time we provide single cell data on olfactory mucosa in Alzheimers disease for investigating molecular and cellular mechanisms associated with the disease.


title: Glycolic acid protects neurons against ischemia	in vitro and in two animal models of stroke

abstract: Stroke is the second leading cause of death and disability worldwide. Current treatments, such as pharmacological thrombolysis or mechanical thrombectomy, re-open occluded arteries but do not protect against ischemia-induced damage that has already occurred before reperfusion or ischemia/reperfusion-induced neuronal damage. It has been shown that disrupting the conversion of glyoxal to glycolic acid (GA) results in a decreased tolerance to anhydrobiosis in C. elegans, dauer larva, while GA itself can rescue this phenotype. During the process of desiccation/rehydration, a metabolic stop/start similar to the one observed during ischemia/reperfusion occurs. In this study, we tested the protective effect of GA in different ischemia models, including commonly used stroke models in mice and swine. Our results show that GA, given during reperfusion, strongly protects against ischemic damage and improves the functional outcome. We provide evidence that GA exerts its effect by counteracting the glutamate-dependent increase in intracellular calcium during excitotoxicity. These results suggest that GA treatment has the potential to reduce the mortality and disability caused by stroke in patients.


title: A primeval mechanism of tolerance to desiccation based on glycolic acid saves neurons from ischemia in mammals by reducing intracellular calcium-mediated excitotoxicity


title: Acetylcholine Signaling Genes are Required for Cocaine-Stimulated Egg Laying in Caenorhabditis elegans

abstract: The toxicity and addictive liability associated with cocaine abuse are well known. However, its mode of action is not completely understood, and effective pharmacotherapeutic interventions remain elusive. The cholinergic effects of cocaine on acetylcholine receptors, synthetic enzymes, and degradative enzymes have been the focus of relatively little empirical investigation. Due to its genetic tractability and anatomical simplicity, the egg laying circuit of the hermaphroditic nematode, Caenorhabditis elegans, is a powerful model system to precisely examine the genetic and molecular targets of cocaine in vivo. Here, we report a novel cocaine-induced behavioral phenotype in Caenorhabditis elegans, cocaine-stimulated egg laying. In addition, we present the results of an in vivo candidate suppression screen of synthetic enzymes, receptors, degradative enzymes, and downstream components of the intracellular signaling cascades of the main neurotransmitter systems that control Caenorhabditis elegans egg laying. Our results show that cocaine-stimulated egg laying is dependent on acetylcholine synthesis and synaptic release, functional nicotinic acetylcholine receptors, and the Caenorhabditis elegans acetylcholinesterases.


title: Separation and enrichment of sodium-motile bacteria using cost-effective microfluidics.

abstract: Many motile bacteria are propelled by the rotation of flagellar filaments. This rotation is driven by a membrane protein known as the stator-complex, which drives the rotor of the bacterial flagellar motor. Torque generation is powered in most cases by proton transit through membrane protein complexes known as stators, with the next most common ionic power source being sodium. Sodium-powered stators can be studied through the use synthetic chimeric stators that combine parts of sodium- and proton-powered stator proteins. The most well studied example is the use of the sodium powered PomA-PotB chimeric stator unit in the naturally proton-powered E. coli. Here we designed a fluidics system at low cost for rapid prototyping to separate motile and non-motile populations of bacteria while varying the ionic composition of the media and thus the sodium-motive-force available to drive this chimeric flagellar motor. We measured separation efficiencies at varying ionic concentrations and confirmed using fluorescence that our device delivered eight-fold enrichment of the motile proportion of a mixed population. Furthermore, our results showed that we could select bacteria from reservoirs where sodium was not initially present. Overall, this technique can be used to implement selection of highly-motile fractions from mixed liquid cultures, with applications in directed evolution to investigate the adaptation of motility in bacterial ecosystems.


title: Adsorption of Azo Dyes by a Novel Bio-Nanocomposite Based on Whey Protein Nanofibrils and Nano-clay: Equilibrium Isotherm and Kinetic Modeling

abstract:
Excessive discharge of hazardous azo dyes into the aquatic ecosystem is a global environmental concern. Here, we develop a green approach to remediate dye pollutions in water by fabricating an easy-separable bio-nanocomposite, based on whey protein concentrate, its nanofibrils, and montmorillonite nano-clay. To characterize the nanocomposite, we used SEM, FT-IR, XRD, and BET techniques. Nanofibrils lead to a uniform dispersion of montmorillonite in the whey protein matrix and also reinforce the nanocomposite. The adsorption efficacy was monitored in a batch system, using cationic dyes (Chrysoidine-G, Bismarck brown-R), reactive dyes (reactive black-5, reactive orange-16), acid dyes (acid red-88, acid red-114), and direct dyes (direct violet-51, Congo red). This nanocomposite adsorbed different dye classes, cationic dyes quicker (> 82%, after 4 h), and reactive dyes slower. Then, the effect of initial dye concentration, pH, contact time, adsorbent dose, and temperature on Chrysoidine-G adsorption was explored. The adsorbent showed a high removal (>93%) for a wide concentration range of Chrysoidine-G, also acidic pH and higher temperature are more favorable for the process. Equilibrium adsorption parameters were reasonably fitted with a linear (Nernst) isotherm model. The results indicated the existence of an unlimited number of absorption sites, i.e. no saturation was achieved under our experimental conditions (qmax(Exp)= 731 mg/g). Kinetic data were fitted with pseudo-second-order and intra-particle diffusion models. We conclude that this nanocomposite is a green adsorbent with potential use for wastewater treatment and related purposes.

HighlightsO_LIWe produced an easy-separable bio-nanocomposite using whey nanofibrils and MMT, with high adsorption capacity
C_LIO_LINanofibrils help disperse MMT particles uniformly in the WP matrix
C_LIO_LIThe adsorbents performance was compared to the adsorbents in absence of MMT and nanofibrils
C_LIO_LIThis composite adsorbs cationic, anionic, direct and reactive azo dyes with different kinetics
C_LIO_LIAdsorption isotherms and kinetics are studied in detail
C_LI

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title: Chromatin Fiber Folding Represses Transcription and Loop Extrusion in Quiescent Cells

abstract: Determining the conformation of chromatin in cells at the nucleosome level and its relationship to cellular processes has been a central challenge in biology. We show that in quiescent yeast, widespread transcriptional repression coincides with the local compaction of chromatin fibers into structures that are less condensed and more heteromorphic than canonical 30-nanometer forms. Acetylation or substitution of H4 tail residues decompacts fibers and leads to global transcriptional de-repression. Fiber decompaction also increases the rate of loop extrusion by condensin. These findings establish a role for H4 tail-dependent local chromatin fiber folding in regulating transcription and loop extrusion in cells. They also demonstrate the physiological relevance of canonical chromatin fiber folding mechanisms even in the absence of regular 30-nanometer structures.


title: Cortical processing of reference in language revealed by computational models

abstract: Human language processing involves not only combining word meanings in accordance with semantic and syntactic constraints, but also figuring out who and what is being referred to. Here we present a first study towards a mechanistic understanding of the neural basis for referential processing. Using both functional MRI and magnetoencephalography (MEG), we identified a consistent increase of activity in a network spanning the anterior and posterior left middle temporal gyrus and the angular gyrus for pronoun processing during naturalistic listening for both English and Chinese speakers. We then adopted a "reverse-engineering" approach to examine the cognitive processes underlying pronoun resolution. We evaluated the neural fit of three symbolic models that each formalizes a different strand of explanation for pronoun resolution in the cognitive and linguistic literature, as well as two deep neural network models with an LSTM or a Transformer architecture. Our results favor the memory-based symbolic model, suggesting a domain-general mechanism of pronoun resolution that resembles memory retrieval.


title: The structural connectome constrains fast brain dynamics

abstract: Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on the dynamics of this activity. Here, we use magnetoencephalography (MEG) to quantify the extent to which fast neural dynamics in the human brain are constrained by structural connections inferred from diffusion MRI tractography. We characterize the spatio-temporal unfolding of whole-brain activity at the millisecond scale from source-reconstructed MEG data, estimating the probability that any two brain regions will significantly deviate from baseline activity in consecutive time epochs. We find that the structural connectome relates to, and likely affects, the rapid spreading of neuronal avalanches, evidenced by a significant association between these transition probabilities and structural connectivity strengths (r=0.37, p<0.0001). This finding opens new avenues to study the relationship between brain structure and neural dynamics.


title: Dissecting genomic determinants of positive selection with an evolution-guided regression model

abstract: In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald-Kreitman test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the McDonald-Kreitman test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their non-metabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.


title: SpheroidPicker: An Automated 3D cell culture manipulator robot using deep learning

abstract: Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20 % of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, ex vivo 3D cell cultures from the patients own cancer cells have gained importance. We recently evaluated the major advancements and needs of the 3D cell cultures screening field, and we concluded that strictly standardized sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and transfers the most appropriate ones between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.


title: SequenceBouncer: A method to remove outlier entries from a multiple sequence alignment

abstract: Phylogenetic analyses can take advantage of multiple sequence alignments as input. These alignments typically consist of homologous nucleic acid or protein sequences, and the inclusion of outlier or aberrant sequences can compromise downstream analyses. Here, I describe a program, SequenceBouncer, that uses the Shannon entropy values of alignment columns to identify and remove outlier entries in a manner responsive to overall alignment context. I demonstrate the utility of this software using alignments of mammalian reference mitochondrial genomes, bird cytochrome c oxidase-derived sequence barcodes, and COVID-19 sequences.


title: distinct: a novel approach to differential distribution analyses

abstract: We present distinct, a general method for differential analysis of full distributions that is well suited to applications on single-cell data, such as single-cell RNA sequencing and high-dimensional flow or mass cytometry data. High-throughput single-cell data reveal an unprecedented view of cell identity and allow complex variations between conditions to be discovered; nonetheless, most methods for differential expression target differences in the mean and struggle to identify changes where the mean is only marginally affected. distinct is based on a hierarchical non-parametric permutation approach and, by comparing empirical cumulative distribution functions, identifies both differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean. We performed extensive bench-marks across both simulated and experimental datasets from single-cell RNA sequencing and mass cytometry data, where distinct shows favourable performance, identifies more differential patterns than competitors, and displays good control of false positive and false discovery rates. distinct is available as a Bioconductor R package.


title: Weak vestibular response in persistent developmental stuttering and implications for own voice identification

abstract: Speech-motor and psycholinguistic models employ feedback control from an auditory stream corresponding to own voice. Such models underspecify how own voice is identified. It is proposed that own voice is identified through coincidence detection between the neural firing rates arising from deflection of cochlear and vestibular mechanoreceptors by the sound and vibration generated during vocalisation. The coincidence detection is proposed to differ in people who stutter. In an update to the approach-avoidance conflict model of Sheehan (1953, 1975) instances of stuttering are proposed to coincide with uncertainty over an ongoing speech act. Discussion covers speech-induced suppression, auditory scene analysis, and theories of mental content.


title: Sleep is required for odor exposure to consolidate memory and remodel olfactory synapses.

abstract: Animals with complex nervous systems demand sleep for memory consolidation and synaptic remodeling. Here we show that though the Caenorhabditis elegans nervous system has a limited number of neurons and connections, sleep is necessary for both processes. In addition, it is unclear in any system if sleep collaborates with experience to change synaptic connections between specific neurons and whether this ultimately affects behavior. C. elegans neurons have defined synaptic connections and well-described contributions to specific behaviors. We show that spaced odor-training induces long-term memory, and sleep after training is required for long-term memory. Memory consolidation, but not acquisition, requires a pair of interneurons, the AIYs, which play a role in odor-seeking behavior. In worms that have consolidated memory, both sleep and odor conditioning are required to diminish inhibitory synaptic connections between the AWC chemosensory neurons and the AIY interneurons. Thus, we demonstrate in a living organism that sleep is required for events immediately after training that drive memory consolidation and alter synaptic structures.


title: Sleep is required for odor exposure to consolidate memory and remodel olfactory synapses


title: Sparse Epistatic Regularization of Deep Neural Networks for Inferring Fitness Functions

abstract: Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. Expressive models in machine learning (ML), such as deep neural networks (DNNs), can model the nonlinearities in rugged fitness functions, which manifest as high-order epistatic interactions among the mutational sites. However, in the absence of an inductive bias, DNNs overfit to the small number of labeled sequences available for training. Herein, we exploit the recent biological evidence that epistatic interactions in many fitness functions are sparse; this knowledge can be used as an inductive bias to regularize DNNs. We have developed a method for sparse epistatic regularization of DNNs, called the epistatic net (EN), which constrains the number of non-zero coefficients in the spectral representation of DNNs. For larger sequences, where finding the spectral transform becomes computationally intractable, we have developed a scalable extension of EN, which subsamples the combinatorial sequence space uniformly inducing a sparse-graph-code structure, and regularizes DNNs using the resulting greedy optimization method. Results on several biological landscapes, from bacterial to protein fitness functions, show that EN consistently improves the prediction accuracy of DNNs and enables them to outperform competing models which assume other forms of inductive biases. EN estimates all the higher-order epistatic interactions of DNNs trained on massive sequence spaces--a computational problem that takes years to solve without leveraging the epistatic sparsity in the fitness functions.


title: Broad-spectrum antiviral activity of 3D8, a nucleic acid-hydrolyzing single chain variable fragment (scFv), targeting SARS-CoV-2 and multiple coronaviruses in vitro

abstract:
BackgroundThe current pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the etiology of Coronavirus-induced disease 19 (COVID-19) and poses a critical public health threat worldwide. Effective therapeutics and vaccines against multiple coronaviruses remain unavailable. Single chain variable fragment (scFv), a recombinant antibody exhibits broad-spectrum antiviral activity against DNA and RNA viruses owing to its nucleic acid-hydrolyzing property.

ObjectiveThis study is aimed to investigate an antiviral activity of 3D8 scFv against SARS-CoV-2 and other coronaviruses.

Methods3D8, a recombinant scFv antibody was evaluated for antiviral activity against SARS-CoV-2, HCoV-OC43 and PEDV in Vero E6 cell cultures. Viral growth was quantified with quantitative RT-qPCR and plaque assay. Nucleic acid hydrolyzing activity of 3D8 was assessed through abzyme assays of in vitro viral transcripts and cell viability was determined by MTT assay.

Results3D8 inhibited the replication of SARS-CoV-2, human coronavirus OC43 (HCoV-OC43), and porcine epidemic diarrhea virus (PEDV). Our results revealed the prophylactic and therapeutic effects of 3D8 scFv against SARS-CoV-2 in Vero E6 cells. Immunoblot and plaque assays showed the reduction of coronavirus nucleoproteins and infectious particles respectively in 3D8 scFv-treated cells.

ConclusionsThis data demonstrates the broad-spectrum antiviral activity of 3D8 against SARS-CoV-2 and other coronaviruses. Thus, it could be considered a potential antiviral countermeasure against SARS-CoV-2 and zoonotic coronaviruses.


title: Generating complex patterns of gene expression without regulatory circuits

abstract:
Synthetic biology has successfully advanced our ability to design and implement complex, time-varying genetic circuits to control the expression of recombinant proteins. However, these circuits typically require the production of regulatory genes whose only purpose is to coordinate expression of other genes. When designing very small genetic constructs, such as viral genomes, we may want to avoid introducing such auxiliary gene products while nevertheless encoding complex expression dynamics. To this end, here we demonstrate that varying only the placement and strengths of promoters, terminators, and RNase cleavage sites in a computational model of a bacteriophage genome is sufficient to achieve solutions to a variety of basic gene expression patterns. We discover these genetic solutions by computationally evolving genomes to reproduce desired gene expression time-course data. Our approach shows that non-trivial patterns can be evolved, including complex patterns where the relative ordering of genes by abundance changes over time. We find that some patterns are easier to evolve than others, and comparable expression patterns can be achieved via different genetic architectures. Our work opens up a novel avenue to genome engineering via fine-tuning the balance of gene expression and gene degradation rates.

Author summaryViruses that infect bacteria, commonly called bacteriophages, typically have small genomes that encode as few as 10 genes. From the perspective of understanding genome design and regulation, these organisms are important model systems. Similar to cellular species, the genes encoded on a phage genome often must be expressed at different levels and at particular times during the phage lifecycle. Given their unique size constraints, it may be advantageous for phages to accomplish differential gene expression without having to produce a variety of dedicated regulatory molecules--which are frequently encoded on the larger and more complex genomes of free-living species. Here, we use a computational simulation of phage infection coupled with an evolutionary selection algorithm to illustrate that phage genomes can encode complex time-dependent gene expression patterns without the need for dedicated regulatory molecules. We anticipate that this simulation framework may additionally aid future phage genome design and engineering efforts.

category: synthetic biology


title: Efficient GNE myopathy disease modeling with mutation specific phenotypes in human pluripotent stem cells by base editors

abstract: Despite the great potential of disease modeling with the isogenic pairs of human pluripotent stem cells (hPSCs), the extremely low efficiency of precise gene editing in hPSCs remains a technical hurdle for this approach. Herein, we took advantage of currently available base editors (BEs) to epitomize the isogenic disease model from hPSCs. Using this method, we established 14 hPSCs that harbor point mutations on the GNE gene, including four different mutations found in GNE myopathy patients. Due to lesser activation of p53 by BEs than Cas9, a higher editing efficiency with BEs was achieved. Four different mutations in the epimerase or kinase domains of GNE revealed mutation-specific hyposialylation, which was closely correlated to pathological clinical phenotypes. These mutation-specific hyposialylation patterns were evident in GNE protein structure modeling. Furthermore, treatment with a drug candidate currently under clinical trials showed a mutation-specific drug response in GNE myopathy disease models. These data suggest that isogenic disease models from hPSCs using BEs could serve as a useful tool for mimicking the pathophysiology of GNE myopathy and for predicting drug responses.


title: A convolutional neural-network framework for modelling auditory sensory cells and synapses

abstract: In classical computational neuroscience, analytical model descriptions are derived from neuronal recordings to mimic the underlying biological system. These neuronal models are typically slow to compute and cannot be integrated within large-scale neuronal simulation frameworks. We present a hybrid, machine-learning and computational-neuroscience approach that transforms analytical models of sensory neurons and synapses into deep-neural-network (DNN) neuronal units with the same biophysical properties. Our DNN-model architecture comprises parallel and differentiable equations that can be used for backpropagation in neuro-engineering applications, and offers a simulation run-time improvement factor of 70 and 280 on CPU or GPU systems respectively. We focussed our development on auditory neurons and synapses, and show that our DNN-model architecture can be extended to a variety of existing analytical models. We describe how our approach for auditory models can be applied to other neuron and synapse types to help accelerate the development of large-scale brain networks and DNN-based treatments of the pathological system.


title: Monitoring single-cell dynamics of entry into quiescence during an unperturbed lifecycle

abstract: The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that non-monotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein super-assemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.