title: Improving comparability of studies using HCoV-OC43 as a surrogate for SARS-CoV-2

abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has renewed interest in human coronaviruses that cause the common cold, particularly as research with them at biosafety level (BSL)-2 avoids the added costs and biosafety concerns that accompany work with SARS-COV-2, BSL-3 research. One of these, human coronavirus OC43 (HCoV-OC43), is a well-matched surrogate for SARS-CoV-2 because it is also a Betacoronavirus, targets the human respiratory system, is transmitted via respiratory aerosols and droplets and is relatively resistant to disinfectants. Unfortunately, growth of HCoV-OC43 in the recommended human colon cancer (HRT-18) cells does not produce obvious cytopathic effect (CPE) and its titration in these cells requires expensive antibody-based detection. Consequently, multiple quantification approaches for HCoV-OC43 using alternative cell lines exist, which complicates comparison of research results. Hence, we investigated the basic growth parameters of HCoV-OC43 infection in three of these cell lines (HRT-18, human lung fibroblasts (MRC-5) and African green monkey kidney (Vero E6) cells) including the differential development of cytopathic effect (CPE) and explored reducing the cost, time and complexity of antibody-based detection assay. Multi-step growth curves were conducted in each cell type in triplicate at a multiplicity of infection of 0.1 with daily sampling for seven days. Samples were quantified by tissue culture infectious dose50(TCID50)/ml or plaque assay (cell line dependent) and additionally analyzed on the Sartorius Virus Counter 3100 (VC), which uses flow virometry to count the total number of intact virus particles in a sample. We improved the reproducibility of a previously described antibody-based detection based TCID50 assay by identifying commercial sources for antibodies, decreasing antibody concentrations and simplifying the detection process. The growth curves demonstrated that HCoV-O43 grown in MRC-5 cells reached a peak titer of [~]107 plaque forming units/ml at two days post infection (dpi). In contrast, HCoV-OC43 grown on HRT-18 cells required six days to reach a peak titer of [~]106.5 TCID50/ml. HCoV-OC43 produced CPE in Vero E6 cells but these growth curve samples failed to produce CPE in a plaque assay after four days. Analysis of the VC data in combination with plaque and TCID50 assays together revealed that the defective:infectious virion ratio of MRC-5 propagated HCoV-OC43 was less than 3:1 for 1-6 dpi while HCoV-OC43 propagated in HRT-18 cells varied from 41:1 at 1 dpi, to 329:4 at 4 dpi to 94:1 at 7 dpi. These results should enable better comparison of extant HCoV-OC43 study results and prompt further standardization efforts.


title: Improving human coronavirus OC43 (HCoV-OC43) research results comparability in studies using HCoV-OC43 as a surrogate for SARS-CoV-2

category: microbiology


title: Measuring biodiversity from DNA in the air

abstract:
Impacts of the biodiversity crisis far exceed our ability to monitor changes in terrestrial ecosystems. Environmental DNA has revolutionized aquatic biomonitoring, permitting remote population and diversity assessments. Here we demonstrate that DNA from terrestrial animals can now be collected from the air under natural conditions, a ground-breaking advance for terrestrial biomonitoring. Using air samples from a zoological park, where species are spatially confined and unique compared to native fauna, we show that DNA in air can be used to identify the captive species and their potential interactions with local taxa. Air samples contained DNA from 25 species of mammal and bird including 17 known (and distinct) terrestrial zoo species. We also identified food items from air sampled in enclosures and detected four taxa native to the local area, including the Eurasian hedgehog, endangered in the UK, and the muntjac deer, a locally established invasive species. Our data provide evidence that airDNA is concentrated around recently inhabited areas (e.g., indoor enclosures) but that there is dispersal away from the source suggesting an ecology to airDNA movement which highlights the potential for airDNA sampling at distance. Our data clearly demonstrate the profound potential of air as a source of DNA for global terrestrial biomonitoring and ecological analysis.

Significance StatementThe global decline in biodiversity requires rapid non-invasive biomonitoring tools applicable at a global scale. In this study we collect environmental DNA from mammals and birds from air samples collected in a natural setting. Using only air, we identified 25 species of mammal and bird known to be in the area. Our dataset detected species at risk of local extinction and several confirmed predator-prey interactions. This approach will revolutionize terrestrial biodiversity surveys.

category: ecology


title: The most comprehensive annotation of the Krill transcriptome provides new insights for the study of physiological processes and environmental adaptation

abstract: The krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem, as the abundance of its biomass affects trophic levels both below it and above. Major changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of the krill population and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species, and of the molecular mechanisms behind it are urgently needed. The availability of a large body of RNA-seq assays gave us the opportunity to extend the current knowledge of the krill transcriptome, considerably reducing errors and redundancies. Our study covered the entire developmental process, from larval stages to adult individuals, providing information of central relevance for ecological studies. Here we describe the KrillDB2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses specifically targeting genes and molecular processes relevant to krill physiology. KrillDB2 provides in a single resource the most complete collection of experimental data and bioinformatic annotations: it includes an extended catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions such as developmental stages, geographical regions, seasons, and sexes. Finally, it provides initial indications about non-coding RNAs, a class of molecules whose contribute to krill physiology has never been reported before.


title: Functional and Structural Segregation of Overlapping Helices in HIV-1

abstract: Overlapping coding regions balance selective forces between multiple genes. One possible division of nucleotide sequence is that the predominant selective force on a particular nucleotide can be attributed to just one gene. While this arrangement has been observed in regions in which one gene is structured and the other is disordered, we sought to explore how overlapping genes balance constraints when both protein products are structured over the same sequence. We use a combination of sequence analysis, functional assays and selection experiments to examine an overlapped region in HIV-1 that encodes helical regions in both Env and Rev. We find that functional segregation occurs even in this overlap, with each protein spacing its functional residues in a manner that allows a mutable non-binding face of one helix to encode important functional residues on a charged face in the other helix. Additionally, our experiments reveal novel and critical functional residues in Env and have implications for the therapeutic targeting of HIV-1.

category: evolutionary biology


title: Effects of a 33-sequential beam galactic cosmic ray analog on male mouse behavior and evaluation of CDDO-EA as a radiation countermeasure

abstract: In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a  vehicle formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures.

category: animal behavior and cognition


title: Effects of a 33-ion sequential beam galactic cosmic ray analog on male mouse behavior and evaluation of CDDO-EA as a radiation countermeasure


title: Towards a cumulative science of prosody in autism: a cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children

abstract:
Acoustic atypicalities in speech production are argued to be potential markers of clinical features in Autism Spectrum Disorder (ASD). A recent meta-analysis highlighted shortcomings in the field, in particular small sample sizes and study heterogeneity (Fusaroli et al., 2017). We showcase a cumulative (i.e., explicitly building on previous studies both conceptually and statistically) yet self-correcting (i.e., critically assessing the impact of cumulative statistical techniques) approach to prosody in ASD to overcome these issues.

We relied on the recommendations contained in the meta-analysis to build and analyze a cross-linguistic corpus of multiple speech productions in 77 autistic and 72 neurotypical children and adolescents (>1000 recordings in Danish and US English). We used meta-analytically informed and skeptical priors, with informed priors leading to more generalizable inference. We replicated findings of a minimal cross-linguistically reliable distinctive acoustic profile for ASD (higher pitch and longer pauses) with moderate effect sizes. We identified novel reliable differences between the two groups for normalized amplitude quotient, maxima dispersion quotient, and creakiness. However, the differences were small, and there is likely no one acoustic profile characterizing all autistic individuals. We identified reliable relations of acoustic features with individual differences (age, gender), and clinical features (speech rate and ADOS sub-scores).

Besides cumulatively building our understanding of acoustic atypicalities in ASD, the study shows how to use systematic reviews and meta-analyses to guide the design and analysis of follow-up studies. We indicate future directions: larger and more diverse cross-linguistic datasets, focus on heterogeneity, self-critical cumulative approaches and open science.

Lay SummaryAutistic individuals are reported to speak in distinctive ways. Distinctive vocal production can affect social interactions and social development and could represent a noninvasive way to support the assessment of ASD. We systematically checked whether acoustic atypicalities highlighted in previous articles could be actually found across multiple recordings and two languages. We find a minimal acoustic profile of ASD: higher pitch, longer pauses, increased hoarseness and creakiness of the voice. However, there is much individual variability (by age, sex, language, and clinical characteristics). This suggests that the search for one common "autistic voice" might be naive and more fine-grained approaches are needed.

category: bioinformatics


title: Towards a cumulative science of vocal markers of autism: a cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children


title: Single-Molecule Manipulation of Macromolecules on Membranes Using High-Resolution Optical Tweezers

abstract: Despite their wide applications into soluble macromolecules, optical tweezers have rarely been used to characterize dynamics of membrane proteins, mainly due to lack of model membranes compatible with optical trapping. Here, we found that optical tweezers can stably trap giant unilamellar vesicles (GUVs) containing iodixanol with controlled membrane tension, which can potentially serve as a model membrane to study dynamics of membranes, membrane proteins, or their interactions. We also observed that small unilamellar vesicles (SUVs) are rigid enough to resist large pulling force and offer potential advantages to pull membrane proteins. To demonstrate the use of both model membranes, we pulled membrane tethers from the trapped GUVs and measured the folding or binding dynamics of a single DNA hairpin or synaptotagmin-1 C2 domain attached to the GUV or SUV with high spatiotemporal resolution. Our methodologies facilitate single-molecule manipulation studies of membranes or membrane proteins using optical tweezers.

category: biophysics


title: Gut microbiota-based vaccination engages innate immunity to improve blood glucose control in obese mice

abstract: Obesity and diabetes increase circulating levels of microbial components derived from the gut microbiota. Individual bacterial factors (i.e., postbiotics) can have opposing effects on metabolic inflammation and blood glucose control. We tested the net effect of gut bacterial extracts on blood glucose using a microbiota-based vaccination strategy in mice. Male and female mice had improved insulin sensitivity and blood glucose control five weeks after a single subcutaneous injection of a specific dose of a bacterial extract obtained from the luminal contents of the proximal gut. Injection of mice with proximal gut extracts from germ-free mice revealed that bacteria were required for a microbiota-based vaccination to improve blood glucose control. Vaccination of Nod1-/-, Nod2-/-, and Ripk2-/- mice showed that each of these innate immune proteins was required for bacterial extract injection to improve blood glucose control. A microbiota-based vaccination promoted a proximal gut immunoglobulin-G (IgG) response directed against bacterial extract antigens, where subcutaneous injection of mice with the luminal contents of the ileum elicited a bacterial extract-specific IgG response that is compartmentalized to the ileum of vaccinated mice. A microbiota-based vaccination was associated with an altered the microbiota composition in the ileum and colon of mice. Lean mice required a single injection of proximal gut bacterial extracts, but high fat diet (HFD)-fed, obese mice required prime-boost bacterial extract injections for improvements in blood glucose control. These data show that, upon subversion of the gut barrier, vaccination with proximal gut bacterial extracts engages innate immunity to promote long-lasting improvements in blood glucose control in a dose-dependent manner.

category: physiology


title: Crosstalk between Flavonoids and the Plant Circadian Clock

abstract: Flavonoids are a well-known class of specialized metabolites that play key roles in plant development, reproduction, and survival. Flavonoids are also of considerable interest from the perspective of human health, both as phytonutrients and pharmaceuticals. RNA-Seq analysis of an Arabidopsis null allele for chalcone synthase (CHS), which catalyzes the first step in flavonoid biosynthesis, has uncovered evidence that these compounds influence the expression of circadian clock genes in plants. Analysis of promoter-luciferase constructs showed that the transcriptional activity of genes encoding two components of the central clock, CCA1 and TOC1, across the day/night cycle is altered in CHS-deficient seedlings. The effect of flavonoids on circadian function was furthermore reflected in photosynthetic activity, with chlorophyll cycling abolished in the mutant line. Analysis of a mutant lacking flavonoid 3-hydroxylase (F3H) activity, and thus able to synthesize mono- but not di-hydroxylated B-ring flavonoids, suggests that the latter are at least partially responsible, as further supported by the effects of quercetin on CCA1 promoter activity in wild-type seedlings. Collectively, these experiments point to a previously-unknown connection between flavonoids and circadian cycling in plants and open the way to better understanding of the molecular basis of flavonoid action.

category: plant biology


title: Genome-wide analysis of long terminal repeat retrotransposons from the cranberry Vaccinium macrocarpon

abstract:
BACKGROUNDLong terminal repeat (LTR) retrotransposons are widespread in plant genomes and play a large role in the generation of genomic variation. Despite this, their identification and characterization remains challenging, especially for non-model genomes. Hence, LTR retrotransposons remain undercharacterized in Vaccinium genomes, although they may be beneficial for current berry breeding efforts.

OBJECTIVEExemplarily focusing on the genome of American cranberry (Vaccinium macrocarpon Aiton), we aim to generate an overview of the LTR retrotransposon landscape, highlighting the abundance, transcriptional activity, sequence, and structure of the major retrotransposon lineages.

METHODSGraph-based clustering of whole genome shotgun Illumina reads was performed to identify the most abundant LTR retrotransposons and to reconstruct representative in silico full-length elements. To generate insights into the LTR retrotransposon diversity in V. macrocarpon, we also queried the genome assembly for presence of reverse transcriptases (RTs), the key domain of LTR retrotransposons. Using transcriptomic data, transcriptional activity of retrotransposons corresponding to the consensuses was analyzed.

RESULTSWe provide an in-depth characterization of the LTR retrotransposon landscape in the V. macrocarpon genome. Based on 475 RTs harvested from the genome assembly, we detect a high retrotransposon variety, with all major lineages present. To better understand their structural hallmarks, we reconstructed 26 Ty1-copia and 28 Ty3-gypsy in silico consensuses that capture the detected diversity. Accordingly, we frequently identify association with tandemly repeated motifs, extra open reading frames, and specialized, lineage-typical domains. Based on the overall high genomic abundance and transcriptional activity, we suggest that retrotransposons of the Ale and Athila lineages are most promising to monitor retrotransposon-derived polymorphisms across accessions.

CONCLUSIONSWe conclude that LTR retrotransposons are major components of the V. macrocarpon genome. The representative consensuses provide an entry point for further Vaccinium genome analyses and may be applied to derive molecular markers for enhancing cranberry selection and breeding.


title: Supervised generative design of regulatory DNA forgene expression control

abstract: In order to control gene expression, regulatory DNA variants are commonly designed using random synthetic approaches with mutagenesis and screening. This however limits the size of the designed DNA to span merely a part of a single regulatory region, whereas the whole gene regulatory structure including the coding and adjacent non-coding regions is involved in controlling gene expression. Here, we prototype a deep neural network strategy that models whole gene regulatory structures and generates de novo functional regulatory DNA with prespecified expression levels. By learning directly from natural genomic data, without the need for large synthetic DNA libraries, our ExpressionGAN can traverse the whole sequence-expression landscape to produce sequence variants with target mRNA levels as well as natural-like properties, including over 30% dissimilarity to any natural sequence. We experimentally demonstrate that this generative strategy is more efficient than a mutational one when using purely natural genomic data, as 57% of the newly-generated highly-expressed sequences surpass the expression levels of natural controls. We foresee this as a lucrative strategy to expand our knowledge of gene expression regulation as well as increase expression control in any desired organism for synthetic biology and metabolic engineering applications.

category: synthetic biology


title: Gut microbiome dysbiosis during COVID-19 is associated with increased risk for bacteremia and microbial translocation.

abstract: The microbial populations in the gut microbiome have recently been associated with COVID-19 disease severity. However, a causal impact of the gut microbiome on COVID-19 patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. Antibiotics and other treatments during COVID-19 can potentially confound microbiome associations. We therefore first demonstrate in a mouse model that SARS-CoV-2 infection can induce gut microbiome dysbiosis, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Comparison with stool samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, paralleling our observations in the animal model. Specifically, we observed blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species in hospitalized COVID-19 patients. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data obtained from these patients indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19.


title: Rapid plastic shifts in body size precede and determine population growth

abstract:
O_LIBody size is a fundamental trait linked to many ecological processes--from individuals to ecosystems. Although the effects of body size on metabolism are well-known, the potential reciprocal effects of body size and density are less clear. Specifically, 1) whether changes in body size or density more strongly influence the other and 2) whether coupled rapid changes in body size and density are due to plasticity, rapid evolutionary change, or a combination of both.
C_LIO_LIHere, we address these two issues by experimentally tracking population density and mean body size in the protist Tetrahymena pyriformis as it grows from low density to carrying capacity. We then use Convergent Cross Mapping time series analyses to infer the direction, magnitude, and causality of the link between body size and ecological dynamics. We confirm the results of our analysis by experimentally manipulating body size and density while keeping the other constant. Last, we fit mathematical models to our experimental time series that account for purely plastic change in body size, rapid evolution in size, or a combination of both, to gain insight into the processes that most likely explain the observed dynamics.
C_LIO_LIOur results indicate that changes in body size more strongly influence changes in density than the other way around, but also show that there is reciprocity in this effect (i.e., a feedback). We show that a model that only accounts for purely plastic change in size most parsimoniously explains observed, coupled phenotypic and ecological dynamics.
C_LIO_LITogether, these results suggest 1) that body size can shift dramatically through plasticity, well within ecological timescales, 2) that rapid changes in body size may have a larger effect on ecological dynamics than the reverse, but 3) phenotypic and ecological dynamics influence each as populations grow. Overall, we show that rapid plastic changes in functional traits like body size may play a fundamental -but currently unrecognized- role in familiar ecological processes such as logistic population growth.
C_LI


title: Feedbacks between size and density determine rapid eco-phenotypic dynamics


title: SARS-Cov-2 Spike binding to ACE2 is stronger and longer ranged with glycans

abstract:
Highly detailed steered Molecular Dynamics simulations are performed on differently glycosylated receptor binding domains of the SARS-CoV-2 spike protein. The binding strength and the binding range increases with glycosylation. The interaction energy rises very quickly with pulling the proteins apart and only slowly drops at larger distances. We see a catch slip type behavior where interactions during pulling break and are taken over by new interactions forming. The dominant interaction mode are hydrogen bonds but Lennard-Jones and electrostatic interactions are relevant as well.

Statement of SignificanceGlycosylation of the receptor binding domain of the Spike protein of SARS-CoV-2 as well as the ACE2 receptor leads to stronger and longer ranged binding interactions between the proteins. Particularly, at shorter distances the interactions are between residues of the proteins themselves whereas at larger distances these interactions are mediated by the glycans.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/452507v2_ufig1.gif" ALT="Figure 1">
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title: SARS-Cov-2 Spike binding to ACE2 is stronger and longer ranged due to glycan interaction


title: Ammonium regulates the development and architecture of pine roots through hormonal crosstalk and differential expression of transcription factors in the apex

abstract: Ammonium is a prominent source of inorganic nitrogen for plant nutrition, but excessive amounts can be toxic for many species. However, most conifers are tolerant to ammonium, a relevant physiological feature of this ancient evolutionary lineage. For a better understanding of the molecular basis of this trait, ammonium-induced changes in the transcriptome of maritime pine (Pinus pinaster Ait.) root apex have been determined by laser capture microdissection and RNA sequencing. Ammonium promoted changes in the transcriptional profiles of multiple transcription factors, such as SHORT-ROOT, and phytohormone-related transcripts, such as ACO, involved in the development of the root meristem. Nano-PALDI-MSI and transcriptomic analyses showed that the distributions of IAA and CKs were altered in the root apex in response to ammonium nutrition. Taken together, the data suggest that this early response is involved in the increased lateral root branching and principal root growth, which characterize the long-term response to ammonium supply in pine. All these results suggest that ammonium induces changes in the root system architecture through the IAA-CK-ET phytohormone crosstalk and transcriptional regulation.


title: Revealing Protein-Level Functional Redundancy in the Human Gut Microbiome using Ultra-deep Metaproteomics

abstract:
Functional redundancy is a key property of ecosystems and represents the fact that phylogenetically unrelated taxa can play similar functional roles within an ecosystem. The redundancy of potential functions of human microbiome has been recently quantified using metagenomics data. Yet, the redundancy of functions which are actually expressed within the human microbiome remains largely unexplored. Here, we quantify the protein-level functional redundancy in the human gut microbiome using metaproteomics and network approaches. In particular, our ultra-deep metaproteomics approach revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions. We further examined multiple metaproteomics datasets and showed that various environmental factors, including individuality, biogeography, xenobiotics, and disease, significantly altered the protein-level functional redundancy. Finally, by projecting the bipartite proteomic content networks into unipartite weighted genus networks, functional hub genera across individual microbiomes were discovered, suggesting that there may be a universal principle of functional organization in microbiome assembly.

HighlightsO_LIUltra-deep metaproteomics reveals high protein-level functional redundancy in the human gut microbiome
C_LIO_LIWithin-sample proteomic content networks display universal topology
C_LIO_LIVarious environmental factors influence the redundancy of expressed functions
C_LIO_LIFunctional hub genera are present across different datasets
C_LI

category: systems biology


title: Segmenting and Predicting Musical Phrase Structure Exploits Neural Gain Modulation and Phase Precession

abstract: Music, like language, is characterized by hierarchically organized structure that unfolds over time. Music listening therefore requires not only the tracking of notes and beats but also internally constructing high-level musical structures or phrases and anticipating incoming contents. Unlike for language, mechanistic evidence for online musical segmentation and prediction at a structural level is sparse. We recorded neurophysiological data from participants listening to music in its original forms as well as in manipulated versions with locally or globally reversed harmonic structures. We discovered a low-frequency neural component that modulated the neural rhythms of beat tracking and reliably parsed musical phrases. We next identified phrasal phase precession, suggesting that listeners established structural predictions from ongoing listening experience to track phrasal boundaries. The data point to brain mechanisms that listeners use to segment continuous music at the phrasal level and to predict abstract structural features of music.

category: neuroscience


title: Antagonists targeting eEF2 kinase rescue multiple aspects of pathophysiology in Alzheimer's disease model mice

abstract:
It is imperative to develop novel therapeutic strategies for Alzheimers disease (AD) and related dementia syndromes based on solid mechanistic studies. Maintenance of memory and synaptic plasticity relies on de novo protein synthesis, which is partially regulated by phosphorylation of eukaryotic elongation factor 2 (eEF2) via its kinase eEF2K. Abnormally increased eEF2 phosphorylation and impaired mRNA translation have been linked to AD. We recently reported that prenatal genetic suppression of eEF2K is able to prevent aging-related cognitive deficits in AD model mice, suggesting the therapeutic potential of targeting eEF2K/eEF2 signaling in AD. Here, we tested two structurally distinct small-molecule eEF2K inhibitors in two different lines of AD model mice after onset of cognitive impairments. Our data revealed that treatment with eEF2K inhibitors improved AD-associated synaptic plasticity impairments and cognitive dysfunction, without altering brain amyloid {beta} (A{beta}) and tau pathology. Furthermore, eEF2K inhibition alleviated AD-associated defects in dendritic spine morphology, postsynaptic density formation, protein synthesis, and dendritic polyribosome assembly. Our results may offer critical therapeutic implications for AD, and the proof-of-principle study indicates translational implication of inhibiting eEF2K for AD and related dementia syndromes.

One Sentence SummaryTreatment with eEF2K inhibitors and genetic eEF2K knockout improved cognitive deficits in Alzheimers disease model mice.


title: BAZ2A-RNA mediated association with TOP2A and KDM1A represses gene expression in prostate cancer

abstract: BAZ2A is the epigenetic repressor of rRNA genes that are transcribed by RNA Polymerase I. In prostate cancer (PCa), however, BAZ2A function was shown to go beyond this role since it can also repress other genes that are frequently silenced in metastatic disease. However, the mechanisms of BAZ2A-mediated repression in PCa remain elusive. Here we show that BAZ2A represses genes implicated in PCa through its RNA-binding TAM domain using mechanisms that differ from the silencing of rRNA genes. While TAM domain mediates BAZ2A recruitment to rRNA genes, in PCa cells TAM domain is not required for the association with BAZ2A-regulated genes. Instead, BAZ2A-TAM domain in association with RNA mediates the interaction with the topoisomerase 2A (TOP2A) and the histone demethylase KDM1A, which have been previously implicated in aggressive PCa. TOP2A and KDM1A expression levels positively correlate with BAZ2A levels in both localized and aggressive PCa. Pharmacological inhibition of TOP2A and KDM1A activity upregulates the expression of BAZ2A-repressed genes implicated in PCa that are regulated by a class of inactive enhancers bound by BAZ2A. Our findings indicate that RNA-mediated interactions between BAZ2A and TOP2A and KDM1A regulate gene expression in PCa and may prove to be useful for the stratification of prostate cancer risk and treatment in patients.

category: molecular biology


title: Monitoring the spread of SARS-CoV-2 variants in Moscow and the Moscow region using targeted high-throughput sequencing

abstract: Since the outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 coronavirus, the international community has been concerned about the emergence of mutations that alter the biological properties of the pathogen, for example, increasing its infectivity or virulence. In particular, since the end of 2020, several variants of concern have been identified around the world, including variants "alpha" (B.1.1.7, "British"), "beta" (B.1.351, "South African"), "gamma" (P.1, "Brazilian") and "delta" (B.1.617.2, "Indian"). However, the existing mechanism for searching for important mutations and identifying strains may not be effective enough, since only a relatively small fraction of all identified pathogen samples can be examined for genetic changes by whole genome sequencing due to its high cost. In this study, we used the method of targeted high-throughput sequencing of the most significant regions of the gene encoding the S-glycoprotein of the SARS-CoV-2 virus, for which a primer panel was developed. Using this technique, we examined 579 random samples obtained from patients in Moscow and the Moscow region with coronavirus infection from February to June 2021. The study demonstrated the dynamics of the representation in the Moscow region of a number of SARS-CoV-2 strains and its most significant individual mutations in the period from February to June 2021. It was found that the strain B.1.617.2 began to spread rapidly in Moscow and the Moscow region in May, and in June it became dominant, partially displacing other varieties of the virus. The results obtained make it possible to accurately determine the belonging of the samples to the abovementioned and some other strains. The approach can be used to standardize the procedure for searching for new and existing epidemiologically significant mutations in certain regions of the SARS-CoV-2 genome, which allows studying a large number of samples in a short time and to get a more detailed picture of the epidemiological situation in the region.


title: Nuclear hormone receptors promote gut and glia detoxifying enzyme induction and protect C. elegans from the mold P. brevicompactum

abstract: Animals encounter microorganisms in their habitats, adapting physiology and behavior accordingly. The nematode Caenorhabditis elegans is found in microbe-rich environments; however, its responses to fungi are not extensively studied. Here we describe interactions of C. elegans and Penicillium brevicompactum, an ecologically-relevant mold. Transcriptome studies reveal that co-culture upregulates stress-response genes, including xenobiotic metabolizing enzymes (XMEs), in C. elegans intestine and AMsh glial cells. The nuclear hormone receptors (NHR) NHR-45 and NHR-156 are key induction regulators, and mutants that cannot induce XMEs in the intestine when exposed to P. brevicompactum experience mitochondrial stress and exhibit developmental defects. Different C. elegans wild isolates harbor sequence polymorphisms in nhr-156, resulting in phenotypic diversity in AMsh glia responses to microbe exposure. We propose that P. brevicompactum mitochondria-targeting mycotoxins are deactivated by intestinal detoxification, allowing tolerance to moldy environments. Our studies support the idea that C. elegans NHR gene expansion/diversification underlies adaptation to microbial environments.

category: cell biology


title: Understanding Mechanisms of Chamber-Specific Differentiation Through Combination of Lineage Tracing and Single Cell Transcriptomics

abstract: The specification and differentiation of atrial and ventricular myocardial cell types during development is incompletely understood. We have previously shown that Foxa2 expression during gastrulation identifies a population of ventricular fated progenitors, allowing for labeling of these cells prior to the morphogenetic events that lead to chamber formation and acquisition of bona fide atrial or ventricular identity. In this study, we performed single cell RNA sequencing of Foxa2Cre;mTmG embryos at the cardiac crescent (E8.25), primitive heart tube (E8.75) and heart tube (E9.25) stage in order to understand the transcriptional mechanisms underlying formation of atrial and ventricular cell types at the earliest stages of cardiac development. We find that progression towards differentiated myocardial cell types occurs primarily based on heart field progenitor identity, and that different progenitor populations contribute to ventricular or atrial identity through separate differentiation mechanisms. We identified a number of candidate markers that define such differentiation processes, as well as differential regulation of metabolic processes that distinguish atrial and ventricular fated cells at the earliest stages of development. We further show that exogenous injection with retinoic acid during formation of the cardiac primordia causes defects in ventricular chamber size and is associated with dysregulation in FGF signaling in anterior second heart field cells and a shunt in differentiation towards orthogonal lineages. Retinoic acid also causes defects in cell-cycle exit in myocardial committed progenitors that result in formation of hypomorphic ventricles with decreased expression of important metabolic processes and sarcomere assembly. Collectively, our data identify, at a single cell level, distinct lineage trajectories during cardiac progenitor cell specification and differentiation, and the precise effects of manipulating cardiac progenitor field patterning via exogenous retinoic acid signaling.

category: developmental biology


title: Integrated transcriptomics identifies β-cell subpopulations and genetic networks associated with obesity and glycemic control in SM/J mice

abstract: Understanding how heterogeneous {beta}-cell function and stress response impact diabetic etiology is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some genetic underpinnings driving heterogeneity, but new strategies are required to capture information lost due to technical limitations. Here, we integrate pancreatic islet single-cell and bulk RNA sequencing data to identify {beta}-cell subpopulations based on gene expression and characterize genetic networks associated with {beta}-cell function in high- and low-fat fed male and female SM/J mice at 20 and 30wks of age. Previous studies have shown that high-fat fed SM/J mice resolve glycemic dysfunction between 20 and 30wks. We identify 4 {beta}-cell subpopulations associated with insulin secretion, hypoxia response, cell polarity, and stress response. Relative proportions of these cells are influenced by age, sex, and diet. Network analysis identifies fatty acid metabolism and {beta}-cell physiology gene expression modules associated with the hyperglycemic-obese state. We identify subtype-specific expression of Pdyn and Fam151a as candidate regulators of genetic pathways associated with {beta}-cell function in obesity. In sum, this study uses a novel data integration method to explore how {beta}-cells respond to obesity and glycemic stress, helping to define the relationship between {beta}-cell heterogeneity and diabetes, and shedding light on novel genetic pathways with therapeutic potential.

category: genomics


title: Comparative Genome Analysis Reveals Human Pathogenic Potential of ESBL-Escherichia coli Isolated from Swine Microbiomes

abstract:
BackgroundExtended-spectrum {beta}-lactamase-producing E. coli (ESBL-Ec) harbouring virulence genes in the microbiome of food animals could likely threaten human health but is poorly understood in Cameroon and South Africa. Here, we assessed the resistome, virulome and mobilome of ESBL-Ec isolated from swine microbiomes in these countries, using whole genome sequencing (WGS).

Materials/methodsEleven clonally-related phenotypic ESBL-Ec isolates were subjected to WGS. The isolates were de novo assembled using the CLC Genomics Workbench and SPAdes while RAST and PROKKA were used for annotation of the assembled contigs. Prediction of antibiotic resistance genes, virulence factors and plasmids was performed using ResFinder, VirulenceFinder and PlasmidFinder, respectively.

ResultsDiverse STs were detected with sequence types ST2144 and ST88 predominating and blaCTX-M-15 (55%) as principal ESBL genes. Although the isolates belonged mainly to commensal phylogroups A/B1 (45/28.3%) and C (18.18%), all harboured at least three extraintestinal pathogenic E. coli (ExPEC) VFs with one isolate harbouring up to 18 ExPEC VFs.

ConclusionThe resistance and pathogenic potential of ESBL-Ec colonizing the gut microbiota of swine in both countries demonstrate the urgent need to implement effective strategies to contain the dissemination of virulent ESBL-Ec through the food chain in Cameroon and South Africa.


title: A coordinated function of lncRNA HOTTIP and miRNA-196b underpinning leukemogenesis by targeting Fas signaling

abstract: MicroRNAs (miRNAs) may modulate more than 60% of human coding genes and act as negative regulators, while long non-coding RNAs (lncRNAs) regulate gene expression on multiple levels by interacting with chromatin, functional proteins, and RNAs such as mRNAs and microRNAs. However, the crosstalk between lncRNA HOTTIP and miRNAs in leukemogenesis remains elusive. Using combined integrated analyses of global miRNA expression profiling and state-of-the-art genomic analyses of chromatin such as ChIRP-seq., (genome wide HOTTIP binding analysis), ChIP-seq., and ATAC-seq., we found that miRNA genes are directly controlled by HOTTIP. Specifically, the HOX cluster miRNAs (miR-196a, miR-196b, miR-10a and miR-10b), located cis & trans, were most dramatically regulated and significantly decreased in HOTTIP-/- AML cells. HOTTIP bound to the miR-196b promoter, and HOTTIP deletion reduced chromatin accessibility and enrichment of active histone modifications at HOX cluster associated miRNAs in AML cells, while reactivation of HOTTIP restored miR gene expression and chromatin accessibility in the CTCF-boundary-attenuated AML cells. Inactivation of HOTTIP or miR-196b promotes apoptosis by altering the chromatin signature at the FAS promoter and increasing FAS expression. Transplantation of miR-196b knockdown MOLM13 cells in NSG mice increased overall survival compared to wild-type cells. Thus, HOTTIP remodels the chromatin architecture around miRNAs to promote their transcription, consequently repressing tumor suppressors and promoting leukemogenesis.

category: biochemistry


title: Decellularized Normal and Tumor Scaffolds for Cancer Organoid Cultures as a Model of Colorectal Peritoneal Metastases

abstract:
Peritoneal metastases (PM) from colorectal cancer (CRC) are associated with poor survival. The extracellular matrix (ECM) plays a fundamental role in modulating the homing of CRC metastases to the peritoneum. The mechanisms underlying the interactions between metastatic cells and the ECM, however, remain poorly understood and the number of in vitro models available for the study of the peritoneal metastatic process is limited. Here, we show that decellularized ECM of the peritoneal cavity allows the growth of organoids obtained from PM, favoring the development of three-dimensional nodules that maintain the characteristics of in vivo PM. Organoids preferentially grow on scaffolds obtained from neoplastic peritoneum, which are characterized by greater stiffness than normal scaffolds. A gene expression analysis of organoids grown on different substrates reflected faithfully the clinical and biological characteristics of the organoids. An impact of the ECM on the response to standard chemotherapy treatment for PM was also observed.

SignificanceEvidence of the value of ex vivo 3D models obtained by combining patient-derived extracellular matrices depleted of cellular components and organoids to mimic the metastatic niche, to be used as a tool to develop new therapeutic strategies in a biologically relevant context, to personalize treatments and increase their efficacy.

category: cancer biology


title: Decellularized Normal and Tumor Extracellular Matrix as Scaffold for Cancer Organoid Cultures of Colorectal Peritoneal Metastases


title: Supra-physiological levels of Gibberellins/DELLAs alter the patterning, morphology and abundance of root hairs in root tips of A. thaliana seedlings

abstract: In spite of the known role of gibberellins (GAs), and of their antagonistic proteins, the DELLAs, in leaf hair production, no investigations, however, have assessed their hypothetical function in the production of root hairs. To this aim, the effects of supra-physiological levels of GAs/DELLAs on the spatial patterning of gene expression of the root hair (CPC) and root non-hair (GL2, EGL3 and WER) epidermal cell fate markers, as well as on the distribution, morphology and abundance of root hairs, were studied in root tips of 5-day-old A. thaliana seedlings. Results showed that excessive levels of GAs/DELLAs impaired the spatial patterning of gene expression of the root hair/non-hair epidermal cell fate markers, as well as the arrangement, shape and frequency of root hairs, giving rise to ectopic hairs and ectopic non-hairs, two-haired cells, two-tipped hairs, branched hairs, longer and denser hairs near the root tip under excessive DELLAs, and shorter and scarcer hairs near the root tip under excessive GAs. However, when the gai-1 (GA-insensitive-1) DELLA mutant protein was specifically over-expressed at the root epidermis, no changes in the patterning or abundance of root hairs occurred. Thus, these results suggest that, in seedlings of A. thaliana, the GAs/DELLAs might have a role in regulating the patterning, morphology and abundance of root hairs by acting from the sub-epidermal tissues of the root.


title: Data-independent acquisition protease-multiplexing enables increased proteome sequence coverage across multiple fragmentation modes

abstract: The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments, however due to the additional analysis time required, it has not been widely adapted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 27% increase non-redundant amino acid detections. Importantly, this resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as proteoform analysis.


title: Synaptic decline precedes dopaminergic neuronal loss in human midbrain organoids harboring a triplication of the SNCA gene

abstract:
1.Increased levels of the protein alpha-synuclein (-syn) are associated with the development of neurodegenerative diseases like Parkinsons disease (PD). In physiological conditions, -syn modulates synaptic plasticity, neurogenesis and neuronal survival. However, its pathogenic accumulation and aggregation results in toxicity and neurodegeneration.

Here, we used a PD patient specific midbrain organoid model derived from induced pluripotent stem cells harboring a triplication in the SNCA gene to study PD-associated phenotypes. The model recapitulates the two main hallmarks of PD, which are -syn aggregation and loss of dopaminergic neurons. Additionally, impairments in astrocyte differentiation were detected. Transcriptomics data indicate that synaptic function is impaired in PD specific midbrain organoids. This is further confirmed by alterations in synapse number and electrophysiological activity. We found that synaptic decline precedes neurodegeneration. Finally, this study substantiates that patient specific midbrain organoids allow a personalized phenotyping, which make them an interesting tool for precision medicine and drug discovery.


title: GPR39 Localization in Aging Human Brain and Correlation of Expression and Polymorphism with Vascular Cognitive Impairment

abstract:
INTRODUCTIONThe pathogenesis of vascular cognitive impairment (VCI) is not fully understood. GPR39, an orphan G-protein coupled receptor, is implicated in neurological disorders but its role in VCI is unknown.

METHODSWe performed GPR39 immunohistochemical analysis in postmortem brain samples from mild cognitive impairment (MCI) and control subjects. DNA was analyzed for GPR39 SNPs, and correlated with white matter hyperintensity (WMH) burden on premortem MRI.

RESULTSGPR39 is expressed in aged human dorsolateral prefrontal cortex, localized to microglia and peri-capillary cells resembling pericytes. GPR39-capillary colocalization, and density of GPR39-expressing microglia was increased in aged brains compared to young. SNP distribution was equivalent between groups; however, homozygous SNP carriers were present only in the MCI group, and had higher WMH volume than WT or heterozygous SNP carriers.

DISCUSSIONGPR39 may play a role in aging-related VCI, and may serve as a therapeutic target and biomarker for the risk of developing VCI.


title: LincRNA-Cox2 functions to regulate inflammation in alveolar macrophages during acute lung injury.

abstract: The respiratory system exists at the interface between our body and the surrounding non-sterile environment; therefore, it is critical for a state of homeostasis to be maintained through a balance of pro- and anti- inflammatory cues. An appropriate inflammatory response is vital for combating pathogens, while an excessive or uncontrolled inflammatory response can lead to the development of chronic diseases. Recent studies show that actively transcribed noncoding regions of the genome are emerging as key regulators of biological processes, including inflammation. LincRNA-Cox2 is one such example of an inflammatory inducible long noncoding RNA functioning to control immune response genes. Here using bulk and single cell RNA-seq, in addition to florescence activated cell sorting, we show that lincRNA-Cox2 is most highly expressed in the lung, particularly in alveolar macrophages where it functions to control immune gene expression following acute lung injury. Utilizing a newly generated lincRNA-Cox2 transgenic overexpressing mouse, we show that it can function in trans to control genes including Ccl3, 4 and 5. This work greatly expands our understanding of the role for lincRNA-Cox2 in host defense and sets in place a new layer of regulation in RNA-immune-regulation of genes within the lung.

category: immunology


title: Evolving social behaviour through selection of single-cell adhesion in Dictyostelium discoideum

abstract:
The social amoeba Dictyostelium discoideum commonly forms chimeric fruiting bodies by aggregation of different strains. Genetic variants that produce a higher proportion of spores are predicted to undercut multicellular organization unless cooperators assort positively. Cell adhesion is considered a primary factor driving such assortment, but evolution of adhesion has not been experimentally connected to changes in social performance. We modified by experimental evolution the properties of individual cells, selecting for higher and lower adhesion to a surface. We then quantified the effects of these changes on fitness (reproductive success), on development (timing and patterns of aggregation) for clonal and chimeric aggregates. In binary chimeras, both evolved lines produce a smaller fraction of spores than the ancestor. Surprisingly, evolution of a single-cell trait thus appears to have produced social cooperators irrespective of whether stronger or weaker adhesion was selected. Examination of development and cell-cell adhesion however revealed two distinct social behaviours, whereby less adhesive cells behave as cheaters in the multicellular bodies. Such differences are captured by a metric for social success that generalizes the classical measure of spore bias by taking into account clonal spore production. Our work shows that cell mechanical interactions can constrain evolution of development and assortment in chimeras, and that elucidation of proximate mechanisms is necessary in order to understand the ultimate emergence of multicellular organization.

Author summaryThe multicellular life cycle of Dictyostelium discoideum is as amazing as puzzling. Genetically different cells commonly co-aggregate, so that collective functions - that repose on cooperation among cells - are constantly threatened by the presence of exploitative variants, commonly called  cheaters. The evolution of cheating and cooperative behaviours is expected to depend on cell adhesion, which influences assortment and thus the capacity of cells to interact preferentially with those having the same social strategy. Here, we use experimental evolution to explore how selection acting on single-cell adhesion impacts social behaviour. Higher levels of cooperation appear to evolve as a result of both increased and decreased adhesion of single cells to a surface. However, such phenotypes are associated to opposite developmental dynamics in chimeric aggregates. Differences in social behaviour are captured if spore production of isolated strains is also considered, confirming the expectation that within the multicellular body of chimeric aggregates cooperative behaviour is associated to stronger adhesion, while early cell segregation undermines the success of less adhesive cells.


title: Minimizing the ex vivo confounds of cell-isolation techniques on transcriptomic profiles of purified microglia

abstract:
Modern molecular neuroscience studies require analysis of specific cellular populations derived from brain tissue samples to disambiguate cell-type specific events. This is particularly true in the analysis of minority glial populations in the brain, such as microglia, which may be obscured in whole tissue analyses. Microglia have central functions in development, aging, and neurodegeneration and are a current focus of neuroscience research. A long-standing concern for glial biologists using in vivo models is whether cell isolation from CNS tissue could introduce ex vivo artifacts in microglia, which respond quickly to changes in the environment. Mouse microglia were purified by magnetic-activated cell sorting (MACS), as well as cytometer- and cartridge-based fluorescence-activated cell sorting (FACS) approaches to compare and contrast performance. The Cx3cr1-NuTRAP mouse model was used here to provide an endogenous fluorescent microglial marker and a microglial-specific translatome profile as a baseline comparison lacking cell isolation artifacts. All methods performed similarly for microglial purity with main differences being in cell yield and time of isolation. Ex vivo activation signatures occurred principally during the initial tissue dissociation and cell preparation and not the microglial cell sorting. Utilizing transcriptional and translational inhibitors during the cell preparation prevented the activational phenotype. These data demonstrate that a variety of microglial isolation approaches can be used, depending on experimental needs, and that inhibitor cocktails are effective at reducing cell preparation artifacts.

Table of Contents Image

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/452509v1_ufig1.gif" ALT="Figure 1">
View larger version (19K):
org.highwire.dtl.DTLVardef@823562org.highwire.dtl.DTLVardef@7edb25org.highwire.dtl.DTLVardef@656feeorg.highwire.dtl.DTLVardef@197aae1_HPS_FORMAT_FIGEXP  M_FIG C_FIG Main PointsMACS, cytometer-FACS, and cartridge-FACS give equivalent and sufficient yield/purity for microglial analyses. Ex vivo microglial activation is prevented by supplementation with transcription/translation inhibitors during cell preparation.


title: c-Jun N-terminal kinase (JNK) signaling contributes to cystic burden in polycystic kidney disease

abstract:
Polycystic kidney disease is an inherited degenerative disease in which the uriniferous tubules are replaced by expanding fluid-filled cysts that ultimately destroy organ function. Autosomal dominant polycystic kidney disease (ADPKD) is the most common form, afflicting approximately 1 in 1,000 people. It primarily is caused by mutations in the transmembrane proteins polycystin-1 (Pkd1) and polycystin-2 (Pkd2). The most proximal effects of Pkd mutations leading to cyst formation are not known, but pro-proliferative signaling must be involved for the tubule epithelial cells to increase in number over time. The c-Jun N-terminal kinase (JNK) pathway promotes proliferation and is activated in acute and chronic kidney diseases. Using a mouse model of cystic kidney disease caused by Pkd2 loss, we observe JNK activation in cystic kidneys and observe increased nuclear phospho c-Jun in cystic epithelium. Genetic removal of Jnk1 and Jnk2 suppresses the nuclear accumulation of phospho c-Jun, reduces proliferation and reduces the severity of cystic disease. While Jnk1 and Jnk2 are thought to have largely overlapping functions, we find that Jnk1 loss is nearly as effective as the double loss of Jnk1 and Jnk2. Jnk pathway inhibitors are in development for neurodegeneration, cancer, and fibrotic diseases. Our work suggests that the JNK pathway should be explored as a therapeutic target for ADPKD.

Author SummaryAutosomal dominant polycystic kidney disease is a leading cause of end stage renal disease requiring dialysis or kidney transplant. During disease development, the cells lining the kidney tubules proliferate. This proliferation transforms normally small diameter tubules into fluid-filled cysts that enlarge with time, eventually destroying all kidney function. Despite decades of research, polycystic kidney disease remains incurable. Furthermore, the precise signaling events involved in cyst initiation and growth remain unclear. The c-Jun N-terminal kinase (JNK), is a major pathway regulating cellular proliferation and differentiation but its importance to polycystic kidney disease was not known. We show that JNK activity is elevated in cystic kidneys and that reducing JNK activity decreases cyst growth pointing to JNK inhibition as a therapeutic strategy for treating polycystic kidney disease.

category: genetics


title: Variant calling tool evaluation for variable size indel calling from next generation whole genome and targeted sequencing data

abstract:
Insertions and deletions (indels) in human genomes are associated with a wide range of phenotypes, including various clinical disorders. High-throughput, next generation sequencing (NGS) technologies enable detection of short genetic variants, such as single nucleotide variants (SNVs) and indels. However, the variant calling accuracy for indels remains considerably lower than for SNVs. Here we present a comparative study of the performance of variant calling tools on indel calling, evaluated with a wide repertoire of NGS datasets. While there is no single optimal tool to suit all circumstances, our results demonstrate that the choice of variant calling tool greatly impacts the precision and recall of indel calling. Furthermore, to reliably detect indels, it is essential to choose NGS technologies that offer a long read length and high coverage, coupled with specific variant calling tools.

Author summaryThe development of next generation sequencing (NGS) technologies and computational algorithms enabled large scale, simultaneous detection of wide range of genetic variants, such as single nucleotide variants as well as insertions and deletions (indels), which may confer potential clinical significance. Recently, many studies have been conducted to evaluate variant calling tools on indel calling. However, the optimal indel size range for different variant calling tools remain unclear. A good benchmarking dataset for indel calling evaluation should contain biologically representative high-confident indels with a wide size range and preferably come from various sequencing settings. In this article, we created a semi-simulated whole genome sequencing dataset where the sequencing data was computationally generated. The indels in the semi-simulated genome were incorporated from a real human sample to represent biologically realistic indels and to avoid inclusion of variants due to potential technical sequencing errors. Furthermore, we used three real-world NGS datasets generated by whole genome or targeted sequencing to further evaluate our candidate tools. Our results demonstrated that variant calling tools varies greatly in calling different sizes of indels. Deletion calling and insertion calling also showed differences among the tools. The sequencing settings in coverage and read length also had a great impact on indel calling. Our results suggest that the accurate indel calling was dependent on the combination of a variant calling tool, indel size range and sequencing settings.


title: Model-based identification of conditionally-essential genes from transposon-insertion sequencing data

abstract:
The understanding of bacterial gene function has been greatly enhanced by recent advancements in the deep sequencing of microbial genomes. Transposon insertion sequencing methods combines next-generation sequencing techniques with transposon mutagenesis for the exploration of the essentiality of genes under different environmental conditions. We propose a model-based method that uses regularized negative binomial regression to estimate the change in transposon insertions attributable to gene-environment changes without transformations or uniform normalization. An empirical Bayes model for estimating the local false discovery rate combines unique and total count information to test for genes that show a statistically significant change in transposon counts. When applied to RB-TnSeq (randomized barcode transposon sequencing) and Tn-seq (transposon sequencing) libraries made in strains of Caulobacter crescentus using both total and unique count data the model was able to identify a set of conditionally essential genes for each target condition that shed light on their functions and roles during various stress conditions.

Author summaryTransposon insertion sequencing allows the study of bacterial gene function by combining next-generation sequencing techniques with transposon mutagenesis under different genetic and environmental perturbations. Our proposed regularized negative binomial regression method improves the quality of analysis of this data.


title: MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes

abstract:
Translating in vitro results from experiments with cancer cell lines to clinical applications requires the selection of appropriate cell line models. Here we present MFmap (model fidelity map), a machine learning model to simultaneously predict the cancer subtype of a cell line and its similarity to an individual tumour sample. The MFmap is a semi-supervised generative model, which compresses high dimensional gene expression, copy number variation and mutation data into cancer subtype informed low dimensional latent representations. The accuracy (test set F1 score > 90%) of the MFmap subtype prediction is validated in ten different cancer datasets. We use breast cancer and glioblastoma cohorts as examples to show how subtype specific drug sensitivity can be translated to individual tumour samples. The low dimensional latent representations extracted by MFmap explain known and novel subtype specific features and enable the analysis of cell-state transformations between different subtypes. From a methodological perspective, we report that MFmap is a semi-supervised method which simultaneously achieves good generative and predictive performance and thus opens opportunities in other areas of computational biology.

Author summaryCancer researchers perform experiments with cell lines to better understand the biology of cancer and to develop new anti-cancer treatments. A prerequisite to translate promising results from these in vitro experiments to clinical applications is to use the most appropriate cell line for a given tumour or cancer subtype. We present MFmap (model fidelity map), a deep learning technique to integrate cancer genomic data from patients with cell line data. The MFmap neural network compresses complex genomic features from thousands of genes into a small set of features called latent representations. This makes cell line and tumour data comparable and allows cancer researchers to select the best cell line which closely resembles a specific type of tumours or even an individual tumour. By classifying cancer cell lines into subtypes, MFmap offers a new possibility to predict the effect of therapeutic compounds in a particular tumour subtype. For the example of an aggressive brain tumour we demonstrate that MFmap can be used to study cell-state transformations during the disease course. In addition, MFmap is a promising machine learning method with potential applications in many other areas of biology and medicine.


title: How Axon and Dendrite Branching Are Governed by Time, Energy, and Spatial Constraints

abstract:
Neurons are connected by complex branching processes - axons and dendrites - that collectively process information for organisms to respond to their environment. Classifying neurons according to differences in structure or function is a fundamental part of neuroscience. Here, by constructing new biophysical theory and testing against our empirical measures of branching structure, we establish a correspondence between neuron structure and function as mediated by principles such as time or power minimization for information processing as well as spatial constraints for forming connections. Specifically, based on these principles, we use undetermined Lagrange multipliers to predict scaling ratios for axon and dendrite sizes across branching levels. We test our predictions for radius and length scale factors against those extracted from neuronal images, measured for cell types and species that range from insects to whales. Notably, our findings reveal that the branching of axons and peripheral nervous system neurons is mainly determined by time minimization, while dendritic branching is mainly determined by power minimization. Further comparison of different dendritic cell types reveals that Purkinje cell dendrite branching is constrained by material costs while motoneuron dendrite branching is constrained by conduction time delay over a range of species. Our model also predicts a quarter-power scaling relationship between conduction time delay and species body size, which is supported by experimental data and may help explain the emergence of hemispheric specialization in larger animals as a means to offset longer time delays.

Author summaryNeurons are the basic building blocks of the nervous system, responsible for information processing and communication in animals. They consist of a centralized cell body and two types of processes - axons and dendrites - that connect to one another. Previous studies of the differences among neuron cell types have focused on comparisons of either structure or function separately, without considering combined effects. Based on theory for structure of and flow through biological resource distribution networks, we develop a new model that relates neuron structure to function. We find that differences in structure between axons and dendrites as well as between dendrites of different cell types can be related to differences in function and associated evolutionary pressures. Moreover, using our mathematical model, we find that the conduction time delay of electrical signals systematically varies with species body size - neurons in larger species have longer delays - providing a possible explanation for hemispheric specialization in larger animals.


title: Hypersensitivity of MAIT cells to Leukocidin ED indicates a Staphylococcus aureus immune evasion mechanism targeting the innate effector cell response

abstract: Mucosa-associated invariant T (MAIT) cells recognize bacterial riboflavin metabolite antigens presented by MR1 and play an important role in antimicrobial immune defense. Staphylococcus aureus is a pathobiont expressing a range of virulence factors including the secreted toxin Leukocidin ED (LukED), which binds to certain chemokine receptors and causes cell death by osmolysis. Here, we investigated the effect of LukED on subsets of human T cells and NK cells that are involved in the early innate response to infection. MAIT cells were strikingly hypersensitive to LukED-mediated lysis and rapidly lost from the peripheral blood T cell pool upon exposure to the toxin, leaving a T cell population devoid of MAIT cells. The cytolytic effect of LukED on MAIT cells was rapid, occurred at lower LukED concentration compared to effects on the overall T cell pool, and coincided with extraordinarily high and uniform expression of CCR5. Furthermore, loss of MAIT cells was efficiently inhibited by the CCR5 inhibitor Maraviroc. Interestingly, pre-activation of MAIT cells with IL-12 and IL-18 also partially rescued these cells from LukED toxicity. Among NK cells, LukED targeted the more mature and cytotoxic CD57+ NK cell subset in a CXCR1-dependent manner. Overall, these results indicate that LukED efficiently eliminates cells of the human immune system that have the capacity to respond rapidly to S. aureus in an innate fashion, and that MAIT cells are exceptionally vulnerable to this toxin. Thus, the findings support a model where LukED functions as a S. aureus immune evasion mechanism to avoid recognition by the rapid cell-mediated responses mediated by MAIT cells and NK cells.


title: Inactivation effects of plasma-activated water on Fusarium graminearum

abstract:
The continuous usage of fungicides poses a potential threat to the environment, ranging from mere irritation to being very toxic to human beings and organisms. Plasma-activated water (PAW) has recently gained much interest as a promising candidate to inactivate fungi. However, the inactivation mechanisms of PAW are still not well understood. In this study, the effect of PAW on the viability and the cellular responses of Fusarium graminearum in PAW inactivation were investigated. The results showed that microbial activity of spores was significantly inhibited by PAW treatment (P < 0.05). The symptoms caused by F. graminearum were significantly reduced on the spikelets. Our data indicated that PAW could induce cell wall sculpturing, membrane permeability changes, and mitochondrial dysfunction. Differential gene expression analysis also confirmed that the cell membrane, the cell wall and the mitochondria were the organelles most affected by PAW. The results from this study facilitate the understanding of the mechanisms underlying the responses of F. graminearum to PAW and the development of PAW as a potential fungicidal agent or an effective supplement to fungicides.

HighlightsO_LIThe viability of F. graminearum is notably inhibited by PAW
C_LIO_LIThe symptoms caused by F. graminearum were significantly reduced on the spikelets
C_LIO_LIOxidative stress induce cell wall sculpturing, membrane permeability change
C_LIO_LIPAW can cause the mitochondrial dysfunction
C_LIO_LICell wall, membrane and mitochondria are the most affected organelles by PAW
C_LI

category: microbiology


title: Heterogeneity in the transcriptional response of the human pathogen Aspergillus fumigatus to the antifungal agent caspofungin

abstract: Aspergillus fumigatus is the main causative agent of invasive pulmonary aspergillosis (IPA), a severe disease that affects immunosuppressed patients worldwide. The fungistatic drug caspofungin is the second line therapy against IPA but has increasingly been used against clinical strains that are resistant to azoles, the first line antifungal therapy. In high concentrations, caspofungin induces a tolerance phenotype with partial reestablishment of fungal growth called caspofungin paradoxical effect (CPE), resulting from a change in the composition of the cell wall. An increasing number of studies has shown that different isolates of A. fumigatus exhibit phenotypic heterogeneity, including heterogeneity in their CPE response. To gain insights into the underlying molecular mechanisms of CPE response heterogeneity, we analyzed the transcriptomes of two A. fumigatus reference strains, Af293 and CEA17, exposed to low and high caspofungin concentrations. We found that there is a core transcriptional response that involves genes related to cell wall remodeling processes, mitochondrial function, transmembrane transport, and amino acid and ergosterol metabolism, and a variable response related to secondary metabolite (SM) biosynthesis and iron homeostasis. Specifically, we show here that the overexpression of a SM pathway that works as an iron chelator extinguishes the CPE in both backgrounds, whereas iron depletion is detrimental for the CPE in Af293 but not in CEA17. We next investigated the function of the transcription factor CrzA, whose deletion was previously shown to result in heterogeneity in the CPE response of the Af293 and CEA17 strains. We found that CrzA constitutively binds to and modulates the expression of several genes related to processes involved in caspofungin tolerance, and that crzA deletion differentially impacts the SM production and growth of Af293 and CEA17. As opposed to the {Delta}crzACEA17 mutant, the {Delta}crzAAf293 mutant fails to activate cell wall remodeling genes upon caspofungin exposure, which most likely severely affects its macrostructure and extinguishes its CPE. This work describes how heterogeneity in the response to an antifungal agent between A. fumigatus strains stems from heterogeneity in the function of a transcription factor and its downstream target genes.


title: Mmp-13 deletion in cells of the mesenchymal lineage increases bone mass, decreases endocortical osteoclast number, and attenuates the cortical bone loss caused by estrogen deficiency in mice

abstract: The protective effect of estrogens against cortical bone loss is mediated via direct actions on mesenchymal lineage cells, but functional evidence for the precise molecular mechanism(s) and the mediators of these effects has only recently began to emerge. We report that the matrix metalloproteinase 13 (MMP-13) is the highest up-regulated gene in calvaria or bone marrow cells from mice lacking the estrogen receptor (ER) alpha in osteoprogenitors. We, therefore, generated mice with conditional Mmp-13 deletion in Prrx1 expressing cells (Mmp-13{Delta}Prrx1) and compared the effect of estrogen deficiency on their bone phenotype to that of control littermates (Mmp-13f/f). Femur and tibia length was decreased in sham-operated Mmp-13{Delta}Prrx1 mice as compared to Mmp-13f/f. Cortical thickness and trabecular bone volume in the femur and tibia were increased and osteoclast number at the endocortical surfaces was decreased in the sham-operated female Mmp-13{Delta}Prrx1 mice; whereas bone formation rate was unaffected. Ovariectomy (OVX) caused a decrease of cortical thickness in the femur and tibia of Mmp-13f/f control mice. This effect was attenuated in the Mmp-13{Delta}Prrx1 mice; but the decrease of trabecular bone caused by OVX was not affected. These results reveal that mesenchymal cell-derived MMP-13 regulates osteoclast number, bone resorption, and bone mass. We have recently reported that the loss of cortical, but not trabecular bone, caused by OVX is also attenuated in Cxcl12{Delta}Prrx1 mice. Together with the present report, this functional genetic evidence provides proof of principle that increased production of mesenchymal cell-derived factors, such as CXCL12 and MMP-13, are important mediators of the adverse effect of estrogen deficiency on cortical, but not trabecular, bone. Therefore, the mechanisms responsible for the protective effect of estrogens on these two major bone compartments are different.


title: Limitations of lymphoblastoid cell lines for establishing genetic reference datasets in the immunoglobulin loci

abstract:
Lymphoblastoid cell lines (LCLs) have been critical to establishing genetic resources for biomedical science. They have been used extensively to study human genetic diversity, genome function, and inform the development of tools and methodologies for augmenting disease genetics research. While the validity of variant callsets from LCLs has been demonstrated for most of the genome, previous work has shown that DNA extracted from LCLs is modified by V(D)J recombination within the immunoglobulin (IG) loci, regions that harbor antibody genes critical to immune system function. However, the impacts of V(D)J on data generated from LCLs has not been extensively investigated. In this study, we used LCL-derived short read sequencing data from the 1000 Genomes Project (n=2,504) to identify signatures of V(D)J recombination. Our analyses revealed sample-level impacts of V(D)J recombination that varied depending on the degree of inferred monoclonality. We showed that V(D)J associated somatic deletions impacted genotyping accuracy, leading to adulterated population-level estimates of allele frequency and linkage disequilibrium. These findings illuminate limitations of using LCLs for building genetic resources in the IG loci, with implications for interpreting previous disease association studies in these regions.

Author summaryLymphoblastoid cell lines (LCLs) are cells that have been manipulated to proliferate indefinitely in order to provide a replenishable source of DNA. However, because these cell lines are derived from B cells which have undergone V(D)J recombination they contain somatic deletions within regions of the genome that encode antibody genes. Although several large collaborative projects have utilized DNA from LCLs to generate invaluable genomic resources for the scientific community, the negative impacts of cell line artifacts in these regions of the genome have not been fully appreciated. In this study, we used newly released sequencing data from a large collection of LCLs to determine that the non-inherited artificial deletions within the antibody gene loci can have detrimental effects on downstream genetic analyses.


title: SMC complexes can traverse physical roadblocks bigger than their ring size

abstract:
The ring-shaped structural-maintenance-of-chromosomes (SMC) complexes condensin and cohesin extrude loops of DNA as a key motif in chromosome organization. It remains, how ever, unclear how these SMC motor proteins can extrude DNA loops in chromatin that is bound with proteins. Here, using in vitro single-molecule visualization, we show that nucleosomes, RNA polymerase, and dCas9 pose virtually no barrier to DNA loop extrusion by yeast condensin. Strikingly, we find that even DNA-bound nanoparticles as large as 200 nm, much bigger than the SMC ring size, can be translocated into DNA loops during condensin-driven extrusion. Similarly, human cohesin can pass 200 nm particles during loop extrusion, which even occurs for a single-chain version of cohesin in which the ring-forming subunits are covalently linked and cannot open up to entrap DNA. These findings disqualify all common loop-extrusion models where DNA passes through the SMC rings (pseudo)topologically, and instead point to a nontopological mechanism for DNA loop extrusion.

One-sentence summaryHuge DNA-bound roadblocks can be incorporated into SMC-extruded DNA loops, pointing to a nontopological mechanism for loop extrusion.


title: Plasmin-mediated cleavage of EphA4 at central amygdala inhibitory synapses controls anxiety

abstract: Severe stress can trigger complex behavioural changes such as high anxiety (1). Inhibitory GABA-ergic interneurons in the lateral division of the central amygdala (CEl) control anxiety through feedforward inhibition of their target cells in the medial division (CEm) (2, 3). In particular, PKC{delta}-positive (PKC{delta}+) interneurons in CEl are critical elements of the neuronal circuitry of fear and anxiety (3-5), but the molecular mechanisms they employ are poorly understood. Here, we show that, during stress, GABA-ergic synapses of amygdala PKC{delta}+ interneurons are regulated by a serine protease plasmin. On stress, plasmin cleaves the extracellular portion of the tyrosine kinase receptor EphA4 triggering its dissociation from gephyrin, a postsynaptic GABA-receptor anchoring protein. Dynamic EphA4/gephyrin interaction leads to modification of dendritic spine morphology and synaptic GABA-receptor expression profile. Consistent with the critical role for the plasmin/EphA4/gephyrin signalling axis in anxiogenesis, viral delivery of plasmin-resistant (prEphA4) form of EphA4 into the central amygdala prevents the development of stress-induced anxiety in mice, while the delivery of plasmin-truncated EphA4 (tEphA4) dramatically enhances this effect. Thus, our studies identify a novel, critical molecular cascade regulating GABA-ergic signalling in the central amygdala synapses that allows bidirectional switching of animal behaviour from high to low anxiety states.


title: Exploring the tymovirids landscape through metatranscriptomics data

abstract: Tymovirales is an order of viruses with positive-sense, single-stranded RNA genomes that mostly infect plants, but also fungi and insects. The number of tymovirid sequences has been growing in the last few years with the extensive use of high-throughput sequencing platforms. Here we report the discovery of 31 novel tymovirid genomes associated with 27 different host plant species, which were hidden in public databases. These viral sequences were identified through a homology searches in more than 3,000 plant transcriptomes from the NCBI Sequence Read Archive (SRA) using known tymovirids sequences as query. Identification, assembly and curation of raw SRA reads resulted in 29 viral genome sequences with full-length coding regions, and two partial genomes. Highlights of the obtained sequences include viruses with unique and novel genome organizations among known tymovirids. Phylogenetic analysis showed that six of the novel viruses were related to alphaflexiviruses, seventeen to betaflexiviruses, two to deltaflexiviruses and six to tymoviruses. These findings resulted in the most complete phylogeny of tymovirids to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of viruses. Furthermore, this study illustrates the complexity and diversity of tymovirids genomes and demonstrates that analyzing SRA public data provides an invaluable tool to accelerate virus discovery and refine virus taxonomy.


title: Encoding time in neural dynamic regimes with distinct computational tradeoffs

abstract:
Converging evidence suggests the brain encodes time in time-varying patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Temporal tasks that require producing the same time-dependent output patterns may have distinct computational requirements in regard to the need to exhibit temporal scaling or generalize to novel contexts. It is not known how neural circuits can both encode time and satisfy distinct computational and generalization requirements, it is also not known whether similar patterns of neural activity at the population level can emerge from distinctly different network configurations. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamics for single intervals were associated with fundamentally different encoding strategies and network configurations. Critically, some regimes were better suited for generalization, categorical timing, or robustness to noise. Further analysis revealed different connection patterns underlying the different encoding strategies. Our results predict that apparently similar neural dynamic regimes at the population level can be produced through fundamentally different mechanisms--e.g., in regard to network connectivity and the role of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

Author summaryThe ability to tell time and anticipate when external events will occur are among the most fundamental computations the brain performs. Converging evidence suggests the brain encodes time through changing patterns of neural activity. Different temporal tasks, however, have distinct computational requirements, such as the need to flexibly scale temporal patterns or generalize to novel inputs. To understand how networks can encode time and satisfy different computational requirements we trained recurrent neural networks (RNNs) on two timing tasks that have previously been used in behavioral studies. Both tasks required producing identically timed output patterns. Using a novel framework to quantify how networks encode different intervals, we found that similar patterns of neural activity--neural sequences--were associated with fundamentally different underlying mechanisms, including the connectivity patterns of the RNNs. Critically, depending on the task the RNNs were trained on, they were better suited for generalization, categorical timing, or robustness to noise. Our results predict that similar patterns of neural activity can be produced by distinct RNN configurations, which in turn have fundamentally different computational tradeoffs. Our results also predict that differences in task structure account for some of the experimentally observed variability in how networks encode time.


title: Comprehensive taxon sampling and vetted fossils help clarify the time tree of shorebirds (Aves, Charadriiformes)

abstract: Shorebirds (Charadriiformes) are a globally distributed clade of modern birds and, due to their ecological and morphological disparity, a frequent subject of comparative studies. While molecular phylogenies have been instrumental to resolving the suprafamilial backbone of the charadriiform tree, several higher-level relationships, including the monophyly of plovers (Charadriidae) and the phylogenetic positions of several monotypic families, have remained unclear. The timescale of shorebird evolution also remains uncertain as a result of extensive disagreements among the published divergence dating studies, stemming largely from different choices of fossil calibrations. Here, we present the most comprehensive non-supertree phylogeny of shorebirds to date, based on a total-evidence dataset comprising 336 ingroup taxa (89% of all extant species), 24 loci (15 mitochondrial and 9 nuclear), and 69 morphological characters. Using this phylogeny, we clarify the charadriiform evolutionary timeline by conducting a node-dating analysis based on a subset of 8 loci tested to be clock-like and 16 carefully selected, updated, and vetted fossil calibrations. Our concatenated, species-tree, and total-evidence analyses consistently support plover monophyly and are generally congruent with the topologies of previous studies, suggesting that the higher-level relationships among shorebirds are largely settled. However, several localized conflicts highlight areas of persistent uncertainty within the gulls (Laridae), true auks (Alcinae), and sandpipers (Scolopacidae). At shallower levels, our phylogenies reveal instances of genus-level nonmonophyly that suggest changes to currently accepted taxonomies. Our node-dating analyses consistently support a mid-Paleocene origin for the Charadriiformes and an early diversification for most major subclades. However, age estimates for more recent divergences vary between different relaxed clock models, and we demonstrate that this variation can affect phylogeny-based macroevolutionary studies. Our findings demonstrate the impact of fossil calibration choice on the resulting divergence time estimates, and the sensitivity of diversification rate analyses to the modeling assumptions made in time tree inference.

category: evolutionary biology


title: Mapping inter-individual functional connectivity variability in TMS targets for major depressive disorder

abstract:
Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. We looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We generated individualized E-field maps on the cortical surface for 121 subjects from the Human Connectome Project database using tetrahedral head models generated from T1-weighted MR images. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.

HighlightsO_LIE-field modelling and functional connectivity used to study TMS targets (dlPFC,OFC)
C_LIO_LIConsiderable variability in TMS target E-field patterns seen across subjects
C_LIO_LILarge inter-subject differences in target connectivity observed and characterized
C_LIO_LIMajor functional networks targeted by dlPFC, OFC TMS were the VAN, FPN and DMN
C_LIO_LIInsights can contribute to improved and more personalized TMS therapies in the future
C_LI


title: Effect of the Ecological Location of a Water Source on Entropy and other Spatio-temporal Behavioral Features: An extended and systematic replication

abstract: The continuous analysis of spatial behavioral-dynamics under stimuli-schedules has been a scarcely studied field in experimental psychology. A recent study conducted in our laboratory suggest that the features embedded in the spatial dynamics of behavior are affected by stimulus-schedules, at least, as much as features embedded in discrete responses. In that study we compared the spatial behavioral dynamics under two time-based schedules (fixed vs variable time) of water delivery, and two different locations of water delivery (delivery in central zone vs. perimetral zone) on a Modified Open Field System (MOFS). The present work replicates those findings taking in consideration previously uncontrolled variables. In Experiment 1, three subjects were exposed to a Fixed Time 30s water-delivery schedule. In the first phase the water dispenser was located at the perimetral zone. In the second condition, the water dispenser was located at the central zone. Each location was presented for 20 sessions. In Experiment 2, conditions were the same, but a Variable Time schedule was used. Measures of entropy were used to describe the spatial behavioral dynamics. We found higher levels of entropy under central location of water delivery than in the perimetral location; and higher entropy under Fixed than Variable Time Schedule, confirming previous findings but under different sequences of dispenser locations. In general, a well-differentiated dynamic between experimental conditions was observed in terms of direction (distance to the dispenser) and variation (entropy) of spatial behavior. These findings are discussed under a systemic, parametric, ecological, and non-mediational framework.

category: animal behavior and cognition


title: Modeling transcriptional profiles of gene perturbation with deep neural network

abstract:
BackgroundCell line perturbation data could be utilized as a reference for inferring underlying molecular processes in new gene expression profiles. It is important to develop accurate and computationally efficient algorithms to exploit biological knowledge in the growing compendium of existing perturbation data and harness these for new predictions.

ResultsWe reframed the problem of inferring possible gene perturbation based on a reference perturbation database into a classification task and evaluated the application of deep neural network models to address this problem. Our results showed that a fully-connected multi-layer neural network was able to achieve up to 74.9% accuracy in a holdout test set, but the model generalizability was limited by consistency between training and testing data.

ConclusionCapacity and flexibility enables neural network models to efficiently represent transcriptomic features associated with single gene knockdown perturbations. With consistent signals between training and testing sets, neural networks may be trained to classify new samples to experimentally confirmed molecular phenotypes.

category: bioinformatics


title: NOBIAS: Analyzing anomalous diffusion in single-molecule tracks with nonparametric Bayesian inference

abstract: Single particle tracking (SPT) enables the investigation of biomolecular dynamics at a high temporal and spatial resolution in living cells, and the analysis of these SPT datasets can reveal biochemical interactions and mechanisms. Still, how to make the best use of these tracking data for a broad set of experimental conditions remains an analysis challenge in the field. Here, we develop a new SPT analysis framework: NOBIAS (NOnparametric Bayesian Inference for Anomalous Diffusion in Single-Molecule Tracking), which applies nonparametric Bayesian statistics and deep learning approaches to thoroughly analyze SPT datasets. In particular, NOBIAS handles complicated live-cell SPT data for which: the number of diffusive states is unknown, mixtures of different diffusive populations may exist within single trajectories, symmetry cannot be assumed between the x and y directions, and anomalous diffusion is possible. NOBIAS provides the number of diffusive states without manual supervision, it quantifies the dynamics and relative populations of each diffusive state, it provides the transition probabilities between states, and it assesses the anomalous diffusion behavior for each state. We validate the performance of NOBIAS with simulated datasets and apply it to the diffusion of single outer-membrane proteins in Bacteroides thetaiotaomicron. Furthermore, we compare NOBIAS with other SPT analysis methods and find that, in addition to these advantages, NOBIAS is robust and has high computational efficiency and is particularly advantageous due to its ability to treat experimental trajectories with asymmetry and anomalous diffusion.

category: biophysics