title: The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (Mpro)

abstract:
The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or Mpro, is a promising target for development of novel antiviral therapeutics. Previous X-ray crystal structures of Mpro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded Mpro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these datasets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a temperature-dependent conformational landscape for Mpro, including mobile solvent interleaved between the catalytic dyad, mercurial conformational heterogeneity in a key substrate-binding loop, and a far-reaching intramolecular network bridging the active site and dimer interface. Our results may inspire new strategies for antiviral drug development to counter-punch COVID-19 and combat future coronavirus pandemics.

SynopsisX-ray crystallography at variable temperature for SARS-CoV-2 Mpro reveals a complex conformational landscape, including mobile solvent at the catalytic dyad, mercurial conformational heterogeneity in a key substrate-binding loop, and an intramolecular network bridging the active site and dimer interface.


title: Warming sensitivity of spring phenology of deciduous species lies in their bud energy budget

abstract: Spring phenology is mainly driven by temperature in extratropical ecosystems. Contrasting responses of foliar phenology to climatic warming, however, have been reported in recent decades, raising important questions about the role of other environmental constraints, especially light. In fact, temperatures differ substantially between plant tissues and the air because plants absorb and lose energy. Yet, phenology studies always substitute plant tissue temperature by air temperature. Here, we explored how solar radiation, wind, and bud traits might affect spring phenology of deciduous forests through the energy budget of buds. We show that air temperature might be an imprecise and biased predictor of bud temperature. Our current interpretation of the plant phenological response to warming should be reconsidered, which will require new observations of bud traits and temperature for accurately quantifying their energy budget.

category: ecology


title: scShaper: ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data

abstract: Computational models are needed to infer a representation of the cells, i.e. a trajectory, from single-cell RNA-sequencing data that model cell differentiation during a dynamic process. Although many trajectory inference methods exist, their performance varies greatly depending on the dataset and hence there is a need to establish more accurate, better generalizable methods. We introduce scShaper, a new trajectory inference method that enables accurate linear trajectory inference. The ensemble approach of scShaper generates a continuous smooth pseudotime based on a set of discrete pseudotimes. We demonstrate that scShaper is able to infer accurate trajectories for a variety of nonlinear mathematical trajectories, including many for which the commonly used principal curves method fails. A comprehensive benchmarking with state-of-the-art methods revealed that scShaper achieved superior accuracy of the cell ordering and, in particular, the differentially expressed genes. Moreover, scShaper is a fast method with few hyperparameters, making it a promising alternative to the principal curves method for linear pseudotemporal ordering. scShaper is available as an R package at https://github.com/elolab/scshaper.

category: bioinformatics


title: In silico and in vitro Demonstration of Homoharrintonine Antagonism of RBD-ACE2 Binding and its Anti-inflammatory and anti-thrombogenic Properties in a 3D human vascular lung model

abstract: Since 2019 the world has seen severe onslaught of SARS-CoV-2 viral pandemic. There is an urgent need for drugs that can be used to either prevent or treat the potentially fatal disease COVD-19. To this end, we screened FDA approved antiviral drugs which could be repurposed for COVID-19 through molecular docking approach in the various active sites of receptor binding domain (RBD). The RBD domain of SARS-CoV-2 spike protein is a promising drug target due to its pivotal role in viral-host attachment. Specifically, we focussed on identifying antiviral drugs which could a) block the entry of virus into host cells, b) demonstrate anti-inflammatory and/or anti-thrombogenic properties. Drugs which poses both properties could be useful for prevention and treatment of the disease. While we prioritized a few antiviral drugs based on molecular docking, corroboration with in vitro studies including a new 3D human vascular lung model strongly supported the potential of Homoharringtonine, a drug approved for chronic myeloid leukaemia to be repurposed for COVID-19. This natural product drug not only antagonized the biding of SARS-CoV-2 spike protein RBD binding to human angiotensin receptor 2 (ACE-2) protein but also demonstrated for the first time anti-thrombogenic and anti-leukocyte adhesive properties in a human cell model system. Overall, this work provides an important lead for development of rapid treatment of COVID-19 and also establishes a screening paradigm using molecular modelling and 3D human vascular lung model of disease to identify drugs with multiple desirable properties for prevention and treatment of COVID-19.

category: pharmacology and toxicology


title: Misregulation of MYB16 causes stomatal cluster formation by disrupting polarity in asymmetric cell division

abstract: Stomata and leaf cuticle regulate water evaporation from the plant body and balance the trade-off between photosynthesis and water loss. We identified MYB16, a key transcription factor controlling cutin biosynthesis, from previous stomatal lineage ground cell (SLGC)-enriched transcriptome study. The preferential localization of MYB16 in SLGCs but not meristemoids suggests a link between cutin synthesis and stomatal development. Here, we showed that downregulation of MYB16 in meristemoids was directly mediated by the stomatal master transcription factor, SPEECHLESS (SPCH). The suppression of MYB16 before asymmetric division was crucial for stomatal patterning because overexpression or ectopic expression of MYB16 in meristemoids increased impermeability and elevated stomatal density and clusters. The aberrant pattern of stomata was due to reduced and disrupted establishment of polarity during asymmetric cell division. Manipulating polarity by growing seedlings on hard agar rescued stomatal clusters and polarity defects in MYB16 ectopic lines. By expressing a cutinase in MYB16 ectopic lines, stomatal clustering was reduced, which suggests that the ectopic accumulation of cuticle affects the polarity in asymmetrically dividing cells and causes clustered stomata. Taken together, inhibiting MYB16 expression by SPCH in early stomatal lineage is required to correctly place the polarity complex for proper stomatal patterning during leaf morphogenesis.

category: plant biology


title: ACE2 expression in rat brain: implications for COVID-19 associated neurological manifestations

abstract:
We examined cell type-specific expression and distribution of rat brain angiotensin converting enzyme 2 (ACE2), the receptor for SARS-CoV-2, in rodent brain. ACE2 is ubiquitously present in brain vasculature, with the highest density of ACE2 expressing capillaries found in the olfactory bulb, the hypothalamic paraventricular, supraoptic and mammillary nuclei, the midbrain substantia nigra and ventral tegmental area, and the hindbrain pontine nucleus, pre-Botzinger complex, and nucleus of tractus solitarius. ACE2 was expressed in astrocytes and astrocytic foot processes, pericytes and endothelial cells, key components of the blood-brain-barrier. We found discrete neuronal groups immunopositive for ACE2 in brainstem respiratory rhythm generating centers including the pontine nucleus, the parafascicular/retrotrapezoid nucleus, the parabrachial nucleus, the Botzinger and pre-Botzinger complex and the nucleus of tractus solitarius; in arousal-related pontine reticular nucleus and in gigantocellular reticular nuclei; in brainstem aminergic nuclei, including substantia nigra, ventral tegmental area, dorsal raphe, and locus coeruleus; in the epithalamic habenula, hypothalamic paraventricular and suprammamillary nuclei; and in the hippocampus. Identification of ACE2-expressing neurons in rat brain within well-established functional circuits facilitates prediction of possible neurological manifestations of brain ACE2 dysregulation during and after COVID-19 infection.

HighlightsO_LIACE2 is present in astrocytes, pericytes, and endothelia of the blood brain barrier.
C_LIO_LINeuronal ACE2 expression is shown in discrete nuclei through the brain.
C_LIO_LIBrainstem breathing, arousal-related, hypothalamic and limbic nuclei express ACE2.
C_LIO_LIACE2 is expressed in circuits potentially involved in COVID-19 pathophysiology.
C_LI

category: neuroscience


title: Analysis of caspase-mediated regulation of the cGAS/STING pathway in Kaposi's sarcoma associated herpesvirus lytic infection reveals a dramatic cellular heterogeneity in type I interferon responses

abstract: As a result of the ongoing virus-host arms race, viruses have evolved numerous immune subversion strategies, many of which are aimed at suppressing the production of type I interferons (IFNs)1. This focus on IFN evasion highlights the essential role of these cytokines in controlling viral infections. Apoptotic caspases have recently emerged as important regulators of type I IFN signaling in both non-infectious contexts and during viral infection2-5. Despite being widely considered anti-viral factors since they can trigger cell death, several apoptotic caspases promote viral replication by suppressing innate immune responses2-5. Indeed, we previously discovered that the AIDS-associated oncogenic gammaherpesvirus Kaposis sarcoma-associated herpesvirus (KSHV) exploits caspase-8 activity to suppress the antiviral type I IFN response and promote viral replication5. However, the mechanism of this novel viral immune evasion strategy is poorly understood, particularly how caspase-8 antagonizes IFN signaling during KSHV infection. Here we show that caspase activity inhibits the DNA sensor cGAS6 during KSHV lytic replication to block type I IFN induction. Furthermore, we use single-cell RNA-sequencing to reveal that the potent antiviral state conferred upon caspase inhibition is mediated by an exceptionally small percentage of IFN-{beta}-producing cells, thus uncovering further complexity of IFN regulation during viral infection. Collectively, these results provide insight into multiple levels of cellular type I IFN regulation that viruses co-opt for immune evasion. Unraveling these mechanisms can inform targeted therapeutic strategies for viral infections and reveal cellular mechanisms of regulating interferon signaling in the context of cancer and chronic inflammatory diseases.

category: microbiology


title: Analysis of caspase-mediated suppression of the cGAS/STING pathway in Kaposi's sarcoma associated herpesvirus lytic infection reveals a dramatic cellular heterogeneity in type I interferon responses


title: Optimization of AAV6 transduction enhances site-specific genome editing of primary human lymphocytes

abstract: Adeno-associated virus serotype 6 (AAV6) is a valuable reagent for genome editing of hematopoietic cells due to its ability to serve as a homology donor template. However, a comprehensive study of AAV6 transduction of hematopoietic cells in culture, with the goal of maximizing ex vivo genome editing, has not been reported. Here, we evaluated how the presence of serum, culture volume, transduction time, and electroporation parameters could influence AAV6 transduction. Based on these results, we identified an optimized protocol for genome editing of human lymphocytes based on a short, highly concentrated AAV6 transduction in the absence of serum, followed by electroporation with a targeted nuclease. In human CD4+ T cells and B cells, this protocol improved editing rates up to 7-fold and 21-fold respectively, when compared to standard AAV6 transduction protocols described in the literature. As a result, editing frequencies could be maintained using 50-100-fold less AAV6, which also reduced cellular toxicity. Our results highlight the important contribution of cell culture conditions for ex vivo genome editing with AAV6 vectors and provide a blueprint for improving AAV6-mediated homology-directed editing of human T and B cells.

category: molecular biology


title: H3K27 Acetylated Nucleosomes Facilitate HMGN Protein Localization at Regulatory Sites to Modulate The Interaction of Transcription Factors with Chromatin

abstract: Nucleosomes containing acetylated H3K27 are a major epigenetic mark of active chromatin and identify cell-type specific chromatin regulatory regions which serve as binding sites for transcription factors. Here we show that the ubiquitous nucleosome binding proteins HMGN1 and HMGN2 bind preferentially to H3K27ac nucleosomes at cell-type specific chromatin regulatory regions. HMGNs bind directly to the acetylated nucleosome; the H3K27ac residue and linker DNA facilitate the preferential binding of HMGNs to the modified nucleosomes. Loss of HMGNs increases the levels of H3K27me3 and the histone H1 occupancy at enhancers and promoters and alters the interaction of transcription factors with chromatin. These experiments indicate that the H3K27ac epigenetic mark affects the interaction of architectural protein with chromatin regulatory sites and provide insights into the molecular mechanism whereby ubiquitous chromatin binding proteins, which bind to chromatin without DNA sequence specificity, localize to regulatory chromatin and modulate cell-type specific gene expression.


title: Mitochondrial mutations in Caenorhabditis elegans show signatures of oxidative damage and an AT-bias

abstract: Rapid mutation rates are typical of mitochondrial genomes (mtDNAs) in animals, but it is not clear why. The difficulty of obtaining measurements of mtDNA mutation that are not biased by natural selection has stymied efforts to distinguish between competing hypotheses about the causes of high mtDNA mutation rates. Several studies which have measured mtDNA mutations in nematodes have yielded small datasets with conflicting conclusions about the relative abundance of different substitution classes (i.e. the mutation spectrum). We therefore leveraged Duplex Sequencing, a high-fidelity DNA sequencing technique, to characterize de novo mtDNA mutations in Caenorhabditis elegans. This approach detected nearly an order of magnitude more mtDNA mutations than documented in any previous nematode mutation study. Despite an existing extreme AT bias in the C. elegans mtDNA (75.6% AT), we found that a significant majority of mutations increase genomic AT content. Compared to some prior studies in nematodes and other animals, the mutation spectrum reported here contains an abundance of CG[->]AT transversions, supporting the hypothesis that oxidative damage may be a driver of mtDNA mutations in nematodes. Further, we found an excess of G[->]T and C[->]T changes on the coding DNA strand relative to the template strand, consistent with increased exposure to oxidative damage. Analysis of the distribution of mutations across the mtDNA revealed significant variation among protein-coding genes and as well as among neighboring nucleotides. This high-resolution view of mitochondrial mutations in C. elegans highlights the value of this system for understanding relationships among oxidative damage, replication error, and mtDNA mutation.

category: genetics


title: Fabrication and Evaluation of Mechanical and Tribological Properties of ultra-high-molecular-weight polyethylene-based Nanocomposites Reinforced with Hydroxyapatite, Zirconia and Multi-walled Carbon Nanotubes

abstract: The unique properties of ultra-high-molecular-weight polyethylene (UHMWPE) have made composites based on this polymer the gold standard choice for articulating surfaces used in arthroplasty. However, wear debris released by prosthesis is still a major concern of the implants. In this study, we address the urgent need to revisit the current methodologies used in designing these biomaterials by fabricating UHMWPE-based nanocomposite with Hydroxyapatite (HA), Multi-walled Carbon Nanotubes (MWCNTs), and Zirconia as additives. We investigated how different combinations of these additives impact the nanocomposites hardness, plasticity index (PI), and friction coefficient. Our results show a constant increase in hardness by increasing Zirconia. The MTT assay test and Scanning Electron Microscopy (SEM) demonstrated an increase in cell attachment and cell viability. Examining various additives amounts, we can further explore the possibility of reaching an optimum proportion of the ingredients. Compared with other UHMWPE-based nanocomposites (UHMWPE-HA-MWCNTs), the fabricated nanocomposite shows an improvement in tribological properties.

category: bioengineering


title: Vitamin C inhibits SARS coronavirus-2 main protease essential for viral replication

abstract: There is an urgent need for anti-viral agents that treat and/or prevent Covid-19 caused by SARS-Coronavirus (CoV-2) infections. The replication of the SARS CoV-2 is dependent on the activity of two cysteine proteases, a papain-like protease, PL-pro, and the 3C-like protease known as main protease Mpro or 3CLpro. The shortest and the safest path to clinical use is the repurposing of drugs with binding affinity to PLpro or 3CLpro that have an established safety profile in humans. Several studies have reported crystal structures of SARS-CoV-2 main protease in complex with FDA approved drugs such as those used in treatment of hepatitis C. Here, we report the crystal structure of 3CLpro in complex Vitamin C (L-ascorbate) bound to the proteins active site at 2.5 [A]ngstrom resolution. The crystal structure of the Vitamin C 3CLpro complex may aid future studies on the effect of Vitamin C not only on the coronavirus main protease but on related proteases of other infectious viruses.

category: biophysics


title: Vitamin C Binds to SARS Coronavirus-2 Main Protease Essential for Viral Replication


title: Context Free and Context-Dependent Conceptual Representation in the Temporal Lobes

abstract: How concepts are coded in the brain is a core issue in cognitive neuroscience. Studies have focused on how individual concepts are processed, but the way in which conceptual representation changes to suit the context is unclear. We parametrically manipulated the association strength between words, presented in pairs one word at a time using a slow event-related fMRI design. We combined representational similarity analysis and computational linguistics to probe the neurocomputational content of these trials. Individual word meaning was maintained in supramarginal gyrus (associated with verbal short-term memory) when items were judged to be unrelated, but not when a linking context was retrieved. Context-dependent meaning was instead represented in left lateral prefrontal gyrus (associated with controlled retrieval), angular gyrus and ventral temporal lobe (regions associated with integrative aspects of memory). Analyses of informational connectivity, examining the similarity of activation patterns across trials between sites, showed that control network regions had more similar multivariate responses across trials when association strength was weak, reflecting a common controlled retrieval state when the task required more unusual associations. These findings indicate that semantic control and representational sites amplify contextually-relevant meanings in trials judged to be related.


title: Context Free and Context-Dependent Conceptual Representation in the Brain


title: River phosphorus cycling constrains lake cyanobacteria blooms

abstract: Bioavailable phosphorus exports from rivers during high flow often fuel downstream harmful cyanobacterial blooms; yet whether river phosphorus cycles affect these exports is unclear. Here, we examined river phosphorus cycling during high flow events in a large agricultural watershed that drives cyanobacterial blooms in Lake Erie. We show that between 2003 and 2019 river phosphorus cycles, through phosphorus sorption, reduced bioavailable phosphorus exports by 24%, potentially constraining Lake Erie cyanobacterial blooms by 61%. Over the last 45-years, phosphorus sorption has declined with suspended sediment exports due to increases in soil-erosion-minimizing agricultural practices, likely contributing to recent cyanobacterial blooms. In this, and likely other agricultural watersheds, rivers perform an unrecognized ecosystem service during high flow creating field-river-lake linkages that need to be incorporated into phosphorus management.


title: Re-oxidation of cytosolic NADH is a major contributor to the high oxygen requirements of the thermotolerant yeast Ogataea parapolymorpha in oxygen-limited cultures

abstract:
Thermotolerance is an attractive feature for yeast-based industrial ethanol production. However, incompletely understood oxygen requirements of known thermotolerant yeasts are incompatible with process requirements. To study the magnitude and molecular basis of these oxygen requirements in the facultatively fermentative, thermotolerant yeast Ogataea parapolymorpha, chemostat studies were performed under defined oxygen-sufficient and oxygen-limited cultivation regimes. The minimum oxygen requirements of O. parapolymorpha were found to be at least an order of magnitude larger than those of the thermotolerant yeast Kluyveromyces marxianus. This high oxygen requirement coincided with absence of glycerol formation, which plays a key role in NADH reoxidation in oxygen-limited cultures of other facultatively fermentative yeasts. Co-feeding of acetoin, whose reduction to 2,3-butanediol can reoxidize cytosolic NADH, supported a 2.5-fold higher biomass concentration in oxygen-limited cultures. The apparent inability of O. parapolymorpha to produce glycerol correlated with absence of orthologs of the S. cerevisiae genes encoding glycerol-3P phosphatase (ScGPP1, ScGPP2). Glycerol production was observed in aerobic batch cultures of a strain in which genes including key enzymes in mitochondrial reoxidation of NADH were deleted. However, transcriptome analysis did not identify a clear candidate for the responsible phosphatase. Expression of ScGPD2, encoding NAD+-dependent glycerol-3P dehydrogenase, and ScGPP1 in O. parapolymorpha resulted in increased glycerol production in oxygen-limited chemostats, but glycerol production rates remained substantially lower than observed in S. cerevisiae and K. marxianus. These results identify a dependency on aerobic respiration for reoxidation of NADH generated in biosynthesis as a key factor in the unexpectedly high oxygen requirements of O. parapolymorpha.

ImportanceThermotolerant yeasts hold great potential for anaerobic fermentation processes but their application is so far hampered by incompletely understood oxygen requirements. Based on quantitative physiological studies in oxygen-limited chemostat cultures, this study shows that the thermotolerant yeast Ogataea parapolymorpha has a much higher oxygen requirement than other, previously investigated facultatively fermentative yeasts. The large oxygen requirement of O. parapolymorpha was linked to an inability of oxygen-limited cultures to efficiently reoxidize NADH formed in biosynthetic processes by glycerol formation. These results provide a basis for reducing the oxygen requirements of O. parapolymorpha by targeted metabolic engineering. In addition, this study shows that diversity of oxygen requirements should be taken into account in selecting yeast species for application in anaerobic or oxygen-limited industrial processes.

category: physiology


title: The Immunological Factors Predisposing To Severe COVID-19 Are Already Present In Healthy Elderly And Men

abstract:
BackgroundMale sex and old age are risk factors for COVID-19 severity, but the underlying causes are unknown. A possible explanation for this might be the differences in immunological profiles in males and the elderly before the infection. Given the seasonal profile of COVID-19, the seasonal response against SARS-CoV-2 could also be different in these groups.

MethodsThe abundance of circulating proteins and immune populations associated with severe COVID-19 was analyzed in 2 healthy cohorts. PBMCs of female, male, young, and old subjects in different seasons of the year were stimulated with heat-inactivated SARS-CoV-2.

ResultSeveral T cell subsets, which are known to be depleted in severe COVID-19 patients, were intrinsically less abundant in men and older individuals. Plasma proteins increasing with disease severity, including HGF, IL-8, and MCP-1, were more abundant in the elderly and males. The elderly produced significantly more IL-1RA and had a dysregulated IFN{gamma} response with lower production in the summer compared with young individuals.

ConclusionsThe immune characteristics of severe COVID-19, described by a differential abundance of immune cells and circulating inflammatory proteins, are intrinsically present in healthy men and the elderly. This might explain the susceptibility of men and the elderly to SARS-CoV-2 infection.

SummaryImmunological profile of severe COVID-19, characterized by altered immune cell populations and inflammatory plasma proteins is intrinsically present in healthy men and the elderly. Different age and sex groups show distinct seasonal responses to SARS-CoV-2.

category: immunology


title: Possible role of accessory proteins in the viral replication for the 20I/501Y.V1 (B.1.1.7) SARS-CoV-2 variant

abstract: The study investigates the replication cycle and transcriptional pattern of the B.1.1.7 variant. It was observed that the B.1.1.7 variant required a longer maturation time. The transcriptional response demonstrated higher expression of ORF6 and ORF8 compared to nucleocapsid transcript till the eclipse period which might influence higher viral replication. The number of infectious viruses titer is higher in the B.1.1.7, despite a lesser copy number than B.1, indicating higher infectivity.


title: Mapping of pseudouridine residues on cellular and viral transcripts using a novel antibody-based technique

abstract: Pseudouridine ({Psi}) is the most common non-canonical ribonucleoside present on mammalian non-coding RNAs (ncRNAs), including rRNAs, tRNAs and snRNAs, where it contributes [~]7% of the total uridine level. However, {Psi} constitutes only [~]0.1% of the uridines present on mRNAs and its effect on mRNA function remains unclear. {Psi} residues have been shown to inhibit the detection of exogenous RNA transcripts by host innate immune factors, thus raising the possibility that viruses might have subverted the addition of {Psi} residues to mRNAs by host pseudouridine synthase (PUS) enzymes as a way to inhibit antiviral responses in infected cells. Here, we describe and validate a novel antibody-based {Psi} mapping technique called photo-crosslinking assisted {Psi} sequencing (PA-{Psi}-seq) and use it to map {Psi} residues on not only multiple cellular RNAs but also on the mRNAs and genomic RNA encoded by HIV-1. We describe several 293T-derived cell lines in which human PUS enzymes previously reported to add {Psi} residues to human mRNAs, specifically PUS1, PUS7 and TRUB1/PUS4, were inactivated by gene editing. Surprisingly, while this allowed us to assign several sites of {Psi} addition on cellular mRNAs to each of these three PUS enzymes, the {Psi} sites present on HIV-1 transcripts remained unaffected. Moreover, loss of PUS1, PUS7 or TRUB1 function did not significantly reduce the level of {Psi} residues detected on total human mRNA below the [~]0.1% level seen in wild type cells, thus implying that the PUS enzyme(s) that adds the bulk of {Psi} residues to human mRNAs remains to be defined.


title: The method utilized to purify the SARS-CoV-2 N protein can affect its molecular properties

abstract: One of the main structural proteins of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the nucleocapsid protein (N). The basic function of this protein is to bind genomic RNA and to form a protective nucleocapsid in the mature virion. The intrinsic ability of the N protein to interact with nucleic acids makes its purification very challenging. Therefore, typically employed purification methods appear to be insufficient for removing nucleic acid contamination. In this study, we present a novel purification protocol that enables the N protein to be prepared without any bound nucleic acids. We also performed comparative structural analysis of the N protein contaminated with nucleic acids and free of contamination and showed significant differences in the structural and phase separation properties of the protein. These results indicate that nucleic-acid contamination may severely affect molecular properties of the purified N protein. In addition, the notable ability of the N protein to form condensates whose morphology and behaviour suggest more ordered forms resembling gel-like or solid structures is described.

category: biochemistry


title: Raabin-WBC: a large free access dataset of white blood cells from normal peripheral blood

abstract: Accurate and early detection of peripheral white blood cell anomalies plays a crucial role in the evaluation of an individuals well-being. The emergence of new technologies such as artificial intelligence can be very effective in achieving this. In this regard, most of the state-of-the-art methods use deep neural networks. Data can significantly influence the performance and generalization power of machine learning approaches, especially deep neural networks. To that end, we collected a large free available dataset of white blood cells from normal peripheral blood samples called Raabin-WBC. Our dataset contains about 40000 white blood cells and artifacts (color spots). To reassure correct data, a significant number of cells were labeled by two experts, and the ground truth of nucleus and cytoplasm were extracted by experts for some cells (about 1145), as well. To provide the necessary diversity, various smears have been imaged. Hence, two different cameras and two different microscopes were used. The Raabin-WBC dataset can be used for different machine learning tasks such as classification, detection, segmentation, and localization. We also did some primary deep learning experiments on Raabin-WBC, and we showed how the generalization power of machine learning methods, especially deep neural networks, was affected by the mentioned diversity.


title: Ultrasound stimulation of the motor cortex during tonic muscle contraction

abstract: AO_SCPLOWBSTRACTC_SCPLOWTranscranial ultrasound stimulation (tUS) shows potential as a noninvasive brain stimulation (NIBS) technique, offering increased spatial precision compared to other NIBS techniques. However, its reported effects on primary motor cortex (M1) are limited. We aimed to better understand tUS effects in human M1 by performing tUS of the hand area of M1 (M1hand) during tonic muscle contraction of the index finger. Stimulation during muscle contraction was chosen because of the transcranial magnetic stimulation-induced phenomenon known as cortical silent period (cSP), in which transcranial magnetic stimulation (TMS) of M1hand involuntarily suppresses voluntary motor activity. Since cSP is widely considered an inhibitory phenomenon, it presents an ideal parallel for tUS, which has often been proposed to preferentially influence inhibitory interneurons. Recording electromyography (EMG) of the first dorsal interosseous (FDI) muscle, we investigated effects on muscle activity both during and after tUS. We found no change in FDI EMG activity concurrent with tUS stimulation. Using single-pulse TMS, we found no difference in M1 excitability before versus after sparsely repetitive tUS exposure. Using acoustic simulations in models made from structural MRI of the participants that matched the experimental setups, we estimated in-brain pressures and generated an estimate of cumulative tUS exposure experienced by M1hand for each subject. We were unable to find any correlation between cumulative M1hand exposure and M1 excitability change. We also present data that suggest a TMS-induced MEP always preceded a near-threshold cSP.


title: Gain control by sparse, ultra-slow glycinergic synapses

abstract: SO_SCPLOWUMMARYC_SCPLOWRetinal ON starburst amacrine cells (SACs) play a critical role in computing stimulus direction, partly in service of image stabilization by optokinetic nystagmus. ON SAC responses are sculpted by rich GABAergic innervation, mostly from neighbouring SACs. Surprisingly, however, we find that glycinergic narrow field amacrine cells (NACs) serve as their dominant source of inhibition during sustained activity. Although NAC inputs constitute only [~]5% of inhibitory synapses to ON SACs, their distinct input patterns enable them to drive glycine inhibition during the both light increments and decrements. NAC-to-ON-SAC inhibition appears to be mediated by ultra-slow non-canonical glycine receptors containing the 4 subunit, which effectively summate during repetitive stimulation. Glycinergic inhibition strongly decreases the output gain of the SACs, ensuring that their direction-selective output is maintained over their operating range. These results reveal an unexpected role for glycinergic pathways and receptor kinetics in modulating direction selectivity in the retina.


title: Experimental infection of specific-pathogen-free domestic lambs with Mycoplasma ovipneumoniae causes asymptomatic colonization of the upper airways that is resistant to antibiotic treatment

abstract: Mycoplasma ovipneumoniae (M. ovipneumoniae) is a respiratory pathogen associated with the development of mild to moderate respiratory disease in domestic lambs and severe pneumonia outbreaks in wild ruminants such as bighorn sheep. However, whether M. ovipneumoniae by itself causes clinical respiratory disease in domestic sheep in the absence of secondary bacterial pathogens is still a matter of debate. The goal of our study was to better understand the role of M. ovipneumoniae as a respiratory pathogen in domestic sheep and to explore potential antibiotic treatment approaches. Therefore, we inoculated four-month-old, specific-pathogen-free lambs with field isolates of M. ovipneumoniae and monitored the lambs for eight weeks for colonization with the bacteria, M. ovipneumoniae-specific antibodies, clinical symptoms, and cellular and molecular correlates of lung inflammation. After eight weeks, lambs were treated with the macrolide antibiotic gamithromycin and observed for an additional four weeks. Stable colonization of the upper respiratory tract with M. ovipneumoniae was established in all four M. ovipneumoniae-inoculated, but in none of the four mock-infected lambs. All M. ovipneumoniae-infected lambs developed a robust antibody response to M. ovipneumoniae within 2 weeks. However, we did not observe significant clinical symptoms or evidence of lung damage or inflammation in any of the infected lambs. Interestingly, treatment with gamithromycin failed to reduce M. ovipneumoniae colonization. These observations indicate that, in the absence of co-factors, M. ovipneumoniae causes asymptomatic colonization of the upper respiratory tract of that is resistant to clearance by the host immune response as well as by gamithromycin treatment in domestic lambs.


title: Fixed or random? On the reliability of mixed-effect models for a small number of levels in grouping variables

abstract:
O_LIBiological data are often intrinsically hierarchical. Due to their ability to account for such dependencies, mixed-effects models have become a common analysis technique in ecology and evolution. While many questions around their theoretical foundations and practical applications are solved, one fundamental question is still highly debated: When facing a low number of levels should we model a grouping (blocking, clustering) variable as a random or fixed effect? In such situation, the variance of the random effect is imprecise, but whether this affects the statistical properties of the population effect is unclear.
C_LIO_LIHere, we analyzed the consequences of including a grouping variable as fixed or random effect in the correctly specified and other possible miss-specified models (too simple or too complex models) for data with small number of levels (2 - 8). For all these options, we calculated type I error rates and power. Moreover, we show how these statistical properties change with the study design.
C_LIO_LIWe found that the model choice does not influence the statistical properties of the population effect when the effect is the same at all levels However, if an ecological effect differs among levels, using a random slope and intercept model, and switching to a fixed-effect model only in case of a singular fit, avoids overconfidence in the results. Additionally, power and type I error are strongly influenced by the number of and difference between levels.
C_LIO_LIWe conclude that inferring the correct random effect structure is of high importance to get correct statistical properties. When in doubt, we recommend starting with the simpler model and using model diagnostics to identify missing components. When having identified the correct structure, we encourage to start with a mixed-effects model independent of the number of levels and switch to a fixed-effect model only in case of a singular fit. With these recommendations, we allow for more informative choices about study design and data analysis and thus make ecological inference with mixed-effects models more robust for small number of levels.
C_LI


title: Fixed or random? On the reliability of mixed-effects models for a small number of levels in grouping variables


title: Evaluating Sample Augmentation in Microarray Datasets with Generative Models: A Comparative Pipeline and Insights in Tuberculosis.

abstract: High throughput screening technologies have created a fundamental challenge for statistical and machine learning analyses, i.e., the curse of dimensionality. Gene expression data are a quintessential example, high dimensional in variables (Large P) and comparatively much smaller in samples (Small N). However, the large number of variables are not independent. This understanding is reflected in Systems Biology approaches to the transcriptome as a network of coordinated biological functioning or through principal Axes of variation underlying the gene expression. Recent advances in generative deep learning offers a new paradigm to tackle the curse of dimensionality by generating new data from the underlying latent space captured as a deep representation of the observed data. These have led to widespread applications of approaches such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), especially in domains where millions of data points exist, such as in computer vision and single cell data. Very few studies have focused on generative modeling of bulk transcriptomic data and microarrays, despite being one of the largest types of publicly available biomedical data. Here we review the potential of Generative models in recapitulating and extending biomedical knowledge from microarray data, which may thus limit the potential to yield hundreds of novel biomarkers. Here we review the potential of generative models and conduct a comparative analysis of VAE, GAN and gaussian mixture model (GMM) in a dataset focused on Tuberculosis. We further review whether previously known axes genes can be used as an effective strategy to employ domain knowledge while designing generative models as a means to further reduce biological noise and enhance signals that can be validated by standard enrichment approaches or functional experiments.

category: genomics


title: A proteomics database for CNS proteins of the great pond snail Lymnaea stagnalis

abstract: Applications of key technologies in biomedical research, such as qRT-PCR or LC-MS based proteomics, are generating large biological (-omics) data sets which are useful for the identification and quantification of biomarkers involved in molecular mechanisms of any research area of interest. Genome, transcriptome and proteome databases are already available for a number of model organisms including vertebrates and invertebrates. However, there is insufficient information available for protein sequences of certain invertebrates, such as the great pond snail Lymnaea stagnalis, a model organism that has been used highly successfully in elucidating evolutionarily conserved mechanisms of learning and memory, ageing and age-related as well as amyloid-{beta} induced memory decline. In this investigation, we used a bioinformatics approach to designing and benchmarking a comprehensive CNS proteomics database (LymCNS-PDB) for the identification of proteins from the Central Nervous System (CNS) of Lymnaea stagnalis by LC-MS based proteomics. LymCNS-PDB was created by using the Trinity TransDecoder bioinformatics tool to translate amino acid sequences from mRNA transcript assemblies obtained from an existing published Lymnaea stagnalis transcriptomics database. The blast-style MMSeq2 software was used to match all translated sequences to sequences for molluscan proteins (including Lymnaea stagnalis and other molluscs) available from UniProtKB. LymCNS-PDB, which contains 9,628 identified matched proteins, was then benchmarked by performing LC-MS based proteomics analysis with proteins isolated from the CNS of Lymnaea stagnalis. MS/MS analysis using the LymCNS-PDB database led to the identification of 3,810 proteins while only 982 proteins were identified by using a non-specific Molluscan database. LymCNS-PDB provides a valuable tool that will enable us to perform quantitative proteomics analysis to identify a plethora of protein interactomes involved in several CNS functions in Lymnaea stagnalis including learning and memory, aging-related memory decline and others.


title: A combined bioinformatics and LC-MS based approach for the development and benchmarking of a comprehensive database for CNS proteins in Lymnaea stagnalis


title: LOSS OF PLASMA MEMBRANE LIPID ASYMMETRY CAN INDUCE ORDERED DOMAIN (RAFT) FORMATION

abstract: In some cases lipids in one leaflet of an asymmetric artificial lipid vesicle can suppress formation of ordered lipid domains (rafts) in the opposing leaflet. Whether suppression of domain formation might occur in plasma membranes was studied using plasma membrane vesicles (PMVs) from RBL-2H3 cells. Membrane domain formation and order was assessed by FRET and fluorescence anisotropy. Ordered domains in PMV prepared from cells by N-ethyl maleimide (NEM) treatment formed up to ~37{degrees}C, while ordered domains in symmetric vesicles formed from extracted PMV lipids were stable to 55{degrees}C, indicating that stability of ordered domains was substantially less in intact PMV. This behavior paralleled lesser ordered domain stability in artificial asymmetric lipid vesicles relative to the corresponding symmetric vesicles, suggesting that intact PMV have some degree of lipid asymmetry. This was confirmed by annexin binding showing that NEM PMV are much more asymmetric than PMV formed by dithiothreitol/paraformaldehyde treatment. Stabilization of ordered domain formation, and increased membrane order at low temperature was also observed after detergent solubilization of PMV followed by membrane reconstitution via dilution from detergent, which also should destroy asymmetry, even though membrane proteins remained associated with the reconstituted vesicles. Similar changes in domain formation and membrane order were observed after detergent reconstitution of artificial asymmetric lipid vesicles. PMV ordered domain stability was not increased by digesting peripheral domains of PMV proteins with proteinase K. We conclude loss of PMV lipid asymmetry can induce ordered domain formation. Dynamic control of asymmetry may regulate ordered domain formation in plasma membranes.


title: Revealing cell-fate bifurcations from transcriptomic trajectories of hematopoiesis

abstract: Inspired by Waddingtons illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein the dynamics of an exogenous signal couples to a cells enormously complex signaling and transcriptional machinery, eliciting a qualitative transition in the collective state of a cell - its fate. It remains unclear, however, whether the dynamical systems framework can go beyond a word-based caricature of the system and provide sharp quantitative insights that further our understanding of differentiation. Single-cell RNA sequencing (scRNA-seq), which measures the distributions of possible transcriptional states in large populations of differentiating cells, provides an alternate view, in which development is marked by the individual concentration variations of a myriad of genes. Here, starting from formal mathematical derivations, we challenge these transcriptomic trajectories to a rigorous statistical evaluation of whether they display signatures consistent with bifurcations. After pinpointing bifurcations along transcriptomic trajectories of the neutrophil branch of hematopoeitic differentiation we are able to further leverage the primitive features of a linear instability to identify the single-direction in gene expression space along which the bifurcation unfolds and identify possible gene contributors. This scheme identifies transcription factors long viewed to play a crucial role in the process of neutrophil differentiation in addition to identifying a host of other novel genetic players. Most broadly speaking, we provide evidence that, though very high-dimensional, a bifurcating dynamical systems formalism might be appropriate for the process of cellular differentiation and that it can be leveraged to provide insights. Ambitiously, our work attempts to take a step beyond data-analysis and towards the construction of falsifiable mathematical models that describe the dynamics of the entire transcriptome.


title: A dynamical systems treatment of transcriptomic trajectories in hematopoiesis


title: Structures of the active HER2/HER3 receptor complex reveal dynamics at the dimerization interface induced by binding of a single ligand

abstract: The Human Epidermal Growth Factor Receptor 2 (HER2) and HER3 form a potent pro-oncogenic heterocomplex upon binding of growth factor neuregulin-1{beta} (NRG1{beta})1-3. The mechanism by which HER2 and HER3 interact remains unknown in the absence of any structures of the complex. We isolated the NRG1{beta}-bound near full-length HER2/HER3 dimer and obtained a 2.9[A] cryo-electron microscopy (cryo-EM) reconstruction of the extracellular domain module which reveals unexpected dynamics at the HER2/HER3 dimerization interface. We show that the dimerization arm of NRG1{beta}-bound HER3 is unresolved likely because the apo HER2 monomer fails to undergo a ligand-induced conformational change needed to establish a HER3 dimerization arm binding pocket. In a second structure of an oncogenic extracellular domain mutant of HER2, S310F, we observe a compensatory interaction with the HER3 dimerization arm that stabilizes the dimerization interface. We show that both HER2/HER3 and HER2-S310F/HER3 retain the capacity to bind to the HER2-directed therapeutic antibody, trastuzumab, but the mutant complex does not bind to pertuzumab. Our 3.5[A] structure of the HER2-S310F/HER3/NRG1{beta}/trastuzumab Fragment antigen binding (Fab) complex shows that the receptor dimer undergoes a conformational change to accommodate trastuzumab. Thus, like oncogenic mutations, therapeutics exploit the intrinsic dynamics of the HER2/HER3 heterodimer. The unique features of a singly liganded HER2/HER3 heterodimer underscore the allosteric sensing of the ligand occupancy by the dimerization interface and explain why extracellular domains of HER2 do not homo-associate via canonical active dimer interface.


title: Preparation of Asymmetric Vesicles with Trapped CsCl Avoids Osmotic Imbalance, Non-Physiological External Solutions, and Minimizes Leakage

abstract: The natural asymmetry of cellular membranes influences their properties. In recent years, methodologies for preparing asymmetric vesicles have been developed that rely on the methyl--cyclodextrin catalyzed exchange of lipids between donor lipid multilamellar vesicles and acceptor lipid unilamellar vesicles, and the subsequent separation of the, now asymmetric, acceptor vesicles from the donors. Isolation is accomplished by pre-loading acceptor vesicles with a high concentration of sucrose, typically 25% (w/w), and separating from donor and cyclodextrin by sucrose gradient centrifugation. We found that when the asymmetric vesicles were dispersed under hypotonic conditions using physiological salt solutions, there was enhanced leakage of an entrapped probe, 6-carboxyfluorescein. Studies with symmetric vesicles showed this was due to osmotic pressure and was specific to hypotonic solutions. Inclusion of cholesterol partly reduced leakage but did not completely eliminate it. To avoid having to use hypotonic conditions or to suspend vesicles at non-physiological solute concentrations to minimize leakage, a method for preparing asymmetric vesicles using acceptor vesicle-entrapped CsCl at a physiological salt concentration (100 mM) was developed. Asymmetric vesicles prepared with the entrapped CsCl protocol were highly resistant to 6-carboxyfluorescein.


title: A genetic mouse model with postnatal Nf1 and p53 loss recapitulates the histology and transcriptome of human malignant peripheral nerve sheath tumor

abstract:
BackgroundMalignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas. Somatic inactivation of NF1 and cooperating tumor suppressors, including CDKN2A/B, PRC2, and p53, is found in most MPNST. Inactivation of the LATS1/2 kinases of the Hippo pathway was recently shown to cause tumors resembling MPNST histologically, although Hippo pathway mutations are rarely found in MPNST. Because existing genetically engineered mouse (GEM) models of MPNST do not recapitulate some of the key genetic features of human MPNST, we aimed to establish a mouse MPNST model that recapitulated the human disease genetically, histologically, and molecularly.

MethodsWe combined two genetically modified alleles, an Nf1;Trp53 cis-conditional allele and an inducible Plp-CreER allele (NP-Plp), to model the somatic, possibly postnatal, mutational events in human MPNST. We also generated conditional Lats1;Lats2 knockout mice. We performed histopathologic analysis of mouse MPNST models and transcriptomic comparison of mouse models and human nerve sheath tumors.

ResultsPostnatal Nf1;Trp53 cis-deletion resulted in GEM-MPNST that was histologically more similar to human MPNST than the widely used germline Nf1;Trp53 cis-heterozygous (NPcis) model and showed partial loss of H3K27me3. At the transcriptome level, Nf1;p53-driven GEM-MPNST were distinct from Lats-driven GEM-MPNST and resembled human MPNST more closely than do Lats-driven tumors.

ConclusionsThe NP-Plp model recapitulates human MPNST genetically, histologically, and molecularly.

Key PointsO_LIPostnatal Nf1;p53 cis-deletion in NP-Plp mice results in tumors similar to MPNST.
C_LIO_LIThe transcriptomes of Nf1;p53-driven and Lats-driven MPNST models are distinct.
C_LIO_LINP-Plp model resembles human MPNST genetically, histologically, and molecularly.
C_LI

Importance of the StudyMalignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas with a poor prognosis and limited treatment options. Existing genetically engineered mouse (GEM) models of MPNST do not recapitulate some of the key genetic features of human MPNST. To model the somatic, possibly postnatal, mutational events seen in MPNST patients, we generated a GEM-MPNST model by combining two genetically modified alleles, an Nf1;Trp53 cis-conditional allele and a Plp-CreER allele. Our histologic and transcriptomic analyses showed that this NP-Plp model resembles human MPNST genetically, histologically, and molecularly--more so than the widely used NPcis model and the recently published Lats-driven model. The NP-Plp model is genetically simple, making it easy to maintain and an ideal platform for preclinical studies. Given its tamoxifen-inducible nature, this model can be used to study the time/stage dependency of the tumorigenic potential of Schwann cells.

category: cancer biology


title: Predicting Environmental Chemical Carcinogenicity using a Hybrid Machine-Learning Approach

abstract: Determining environmental chemical carcinogenicity is an urgent need as humans are increasingly exposed to these chemicals. In this study, we determined the carcinogenicity of wide variety real-life exposure chemicals in large scale. To determine chemical carcinogenicity, we have developed carcinogenicity prediction models based on the hybrid neural network (HNN) architecture. In the HNN model, we included new SMILES feature representation method, by modifying our previous 3D array representation of 1D SMILES simulated by the convolutional neural network (CNN). We used 653 molecular descriptors modeled by feed forward neural network (FFNN), and SMILES as chemical features to train the models. We have developed three types of machine learning models: binary classification models to predict chemical is a carcinogenic or non-carcinogenic, multiclass classification models to predict severity of the chemical carcinogenicity, and regression models to predict median toxic dose of the chemicals. Along with the hybrid neural network (HNN) model that we developed, Random Forest (RF), Bootstrap Aggregating (Bagging) and Adaptive Boosting (AdaBoost) methods were also used for binary and multiclass classification. Regression models were developed using HNN, RF, Support Vector Regressor (SVR), Gradient Boosting (GB), Kernel Ridge (KR), Decision Tree with AdaBoost (DT), KNeighbors (KN), and a consensus method. For binary classification, our HNN model predicted with an average accuracy of 74.33% and an average AUC of 0.806, for multiclass classification, the HNN model predicted with an average accuracy of 50.58% and an average micro-AUC of 0.68, and for regression model, the consensus method achieved R2 of 0.40. The predictive performance of our models based on a highly diverse chemicals is comparable to the literature reported models that included the similar and less diverse molecules. Our models can be used in identifying the potentially carcinogenic chemicals for a wide variety of chemical classes.


title: Digital 3D Brain MRI Arterial Territories Atlas

abstract: The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.


title: A multimodal study of a first episode psychosis cohort: potential markers of antipsychotic treatment resistance

abstract: Treatment resistant (TR) psychosis is considered to be a significant cause of disability and functional impairment. Numerous efforts have been made to identify the clinical predictors of TR. However, the exploration of molecular and biological markers is still at an early stage. To understand the TR condition and identify potential molecular and biological markers, we analyzed demographic information, clinical data, structural brain imaging data, and molecular brain imaging data in 7 Tesla magnetic resonance spectroscopy, from a first episode psychosis cohort that includes 138 patients. Age, gender, race, smoking status, duration of illness, and antipsychotic dosages were controlled in the analyses. We found that TR patients had a younger age at onset, more hospitalizations, more severe negative symptoms, a significant reduction in the volumes of the hippocampus (HP) and superior frontal gyrus (SFG), and a significant reduction in glutathione (GSH) levels in the anterior cingulate cortex (ACC), when compared to non-TR patients. The combination of multiple markers provided a better classification between TR and non-TR patients compared to any individual marker. Our study shows that ACC GSH, HP and SFG volumes, and age at onset could potentially be trait biomarkers for TR diagnosis, while hospitalization and negative symptoms could be used to evaluate the progression of the disease. Multimodal cohorts are essential in obtaining a comprehensive understanding of brain disorders.


title: Binocular Mirror-Symmetric Microsaccadic Sampling of Hyperacute 3D-Vision

abstract:
Neural mechanisms behind stereopsis, which requires simultaneous disparity inputs from two eyes, have remained mysterious. Here we show how ultrafast mirror-symmetric photomechanical contractions in the frontal forward-facing left and right eye photoreceptors give Drosophila super-resolution 3D-vision. By interlinking multiscale in vivo assays with multiscale simulations, we reveal how these photoreceptor microsaccades - by verging, diverging and narrowing the eyes overlapping receptive fields - channel depth information, as phasic binocular image motion disparity signals in time. We further show how peripherally, outside stereopsis, microsaccadic sampling tracks a flying flys optic flow field to better resolve the world in motion. These results change our understanding of how insect compound eyes work and suggest a general dynamic stereo-information sampling strategy for animals, robots and sensors.

Significance statementTo move efficiently, animals must continuously work out their x,y,z-positions in respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a new morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila super-resolution 3D-vision and proposes neural computations for accurately predicting these flies depth-perception dynamics, limits, and visual behaviors.


title: Binocular Mirror-Symmetric Microsaccadic Sampling Enables Drosophila Hyperacute 3D-Vision


title: Circadian pacemaker neurons display co-phasic rhythms in basal calcium level and in fast calcium fluctuations

abstract: Circadian pacemaker neurons in the Drosophila brain display daily rhythms in the levels of intracellular calcium. These calcium rhythms are driven by molecular clocks and are required for normal circadian behavior. To study their biological basis, we employed genetic manipulations in conjunction with in vivo light-sheet microscopy to measure calcium dynamics in individual pacemaker neurons over complete 24-hour periods. We found co-phasic daily rhythms in basal calcium levels and in high frequency calcium fluctuations. Further we found that the rhythms of basal calcium levels require the activity of the IP3R, a channel that mediates calcium fluxes from internal endoplasmic reticulum (ER) calcium stores. Independently, the rhythms of fast calcium fluctuations required the T-type voltage-gated calcium channel, a conductance that mediates extracellular calcium influx. These results suggest that Drosophila molecular clocks regulate IP3R and T-type channels to generate coupled rhythms in basal calcium and in fast calcium fluctuations, respectively. We propose that both internal and external calcium fluxes are essential for circadian pacemaker neurons to provide rhythmic outputs, and thereby regulate the activities of downstream brain centers.


title: Stereotypic expansion of Tregulatory and Th17 cells during infancy is disrupted by HIV exposure and gut epithelial damage.

abstract:
Few studies have investigated immune cell ontogeny throughout the neonatal and early paediatric period, where there is often increased vulnerability to infections. Here, we evaluated the dynamics of two critical T cell populations, regulatory (Treg) cells and Th17 cells, over the first 36 weeks of life. Firstly, we observed distinct CD4+ T cells phenotypes between cord blood and peripheral blood, collected within 12 hours of birth, showing that cord blood is not a surrogate for newborn blood. Secondly, both Treg and Th17 cells expanded in a synchronous fashion over 36 weeks of life. However, comparing infants exposed to HIV in utero, but remaining uninfected (iHEU), with HIV-unexposed uninfected control infants (iHUU), there was a lower frequency of peripheral blood Treg cells at birth, resulting in a delayed expansion, and then declining again at 36 weeks. Focusing on birth events, we found that Treg cells co-expressing CCR4 and 4{beta}7 inversely correlated with plasma concentrations of CCL17 (the ligand for CCR4) and intestinal fatty acid binding protein (iFABP), IL-7 and CCL20. This was in contrast to Th17 cells, which showed a positive association with these plasma analytes. Thus, despite the stereotypic expansion of both cell subsets over the first few months of life, there was a disruption in the balance of Th17 to Treg cells at birth likely being a result of gut damage and homing of newborn Treg cells from the blood circulation to the gut.

Key pointsO_LIPhenotypic differences between cord and birth peripheral blood CD4 cells.
C_LIO_LISynchronous increase of Th17-Treg cells is disrupted by HIV/ART exposure.
C_LIO_LIIntrauterine HIV exposure was associated with epithelial gut damage.
C_LI


title: Metagenomic and Metatranscriptomic Analysis Reveals Enrichment for Xenobiotic-Degrading Bacterial Specialists and Xenobiotic-Degrading Genes in a Canadian Prairie Two-Cell Biobed System

abstract: Biobeds are agriculture-based bioremediation tools used to safely contain and microbially degrade on-farm pesticide waste and rinsate, thereby reducing the negative environmental impacts associated with pesticide use. While these engineered ecosystems demonstrate efficient pesticide removal, their microbiome dynamics remain largely understudied both taxonomically and functionally. As such, further characterization of these parameters may aid in the optimization of biobed management and deployment. This study used metagenomic and metatranscriptomic techniques to characterize the microbial community in a two-cell Canadian biobed system before and after a field season of pesticide application. These culture-independent approaches identified an enrichment of xenobiotic-degrading bacteria, such as Afipia, Sphingopyxis and Pseudomonas, and enrichment and transcription of xenobiotic-degrading genes, such as peroxidases, oxygenases, and hydroxylases, among others; we were able to directly link the transcription of these genes to Pseudomonas, Oligotropha, Mesorhizobium, Rhodopseudomonas, and Stenotrophomonas taxa.


title: Generation of SIV resistant T cells and Macrophages from Nonhuman Primate Induced Pluripotent Stem Cells with Edited CCR5 locus

abstract: Adoptive therapies with genetically modified somatic T cells rendered HIV resistant have shown promise for AIDS therapy. A renewable source of HIV resistant human T cells from induced pluripotent stem cells (iPSCs) would further facilitate and broaden the applicability of these therapies. Here, we report successful targeting of the CCR5 locus in iPSCs generated from peripheral blood T cells (T-iPSCs) or fibroblasts (fib-iPSCs) from Mauritian Cynomolgus macaques (MCM), using CRISPR/Cas9 technology. We found that CCR5 editing does not affect pluripotency or hematopoietic and T cell differentiation potentials of fib-iPSCs. However, deletion of CCR5 in T-iPSCs leads to selective loss of their T cell redifferentiation potential without affecting myeloid development. T cells and macrophages produced from CCR5-edited MCM- iPSCs did not support replication of the CCR5-tropic simian immunodeficiency viruses SIVmac239 (T-cell tropic) and SIVmac316 (macrophage-tropic). Overall, these studies provide a platform for further exploration of AIDS therapies based on gene-edited iPSCs in a nonhuman primate preclinical model.

category: cell biology


title: Multi-tissue methylation clocks for age estimation in the common bottlenose dolphin

abstract:
Accurate identification of individual ages within wild bottlenose dolphins (Tursiops truncatus) is critical for determining population health and the development of population management strategies. As such, we analyzed DNA methylation patterns by applying a custom methylation array (HorvathMammalMethyl40) to both blood (n = 140) and skin samples (n = 87) from known age or approximate age (0 to 57 years) bottlenose dolphins. We present three bottlenose dolphin specific age estimation clocks using combined blood and skin (48 CpGs, R = 0.93, median absolute error = 2.13 years), blood only (64 CpGs, R = 0.97, error= 1.46 years) and skin only (39 CpGs, R = 0.95, error= 2.53). Our sex estimator based on 71 CpGs predicts the sex of any odontocete species with 99.5% accuracy. We characterize individual cytosines that correlate with sex and age in dolphins.

The presented epigenetic clocks are expected to be useful for conservation efforts and for studying anthropogenic events.

category: developmental biology


title: Considerations for using reproduction data in toxicokinetic-toxicodynamic modelling

abstract: Toxicokinetic-toxicodynamic (TKTD) modelling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure. These advantages have been recognised in the regulatory arena, especially for environmental risk assessment (ERA) of pesticides, where time-varying exposure is the norm. We critically evaluate the link between the modelled variables in TKTD models and the observations from laboratory ecotoxicity tests. For the endpoint reproduction, this link is far from trivial. The relevant TKTD models for sub-lethal effects are based on Dynamic-Energy Budget (DEB) theory, which specifies a continuous investment flux into reproduction. In contrast, experimental tests score egg or offspring release by the mother. The link between model and data is particularly troublesome when a species reproduces in discrete clutches, and even more so when eggs are incubated in the mothers brood pouch (and release of neonates is scored in the test). This situation is quite common among aquatic invertebrates (e.g., cladocerans, amphipods, mysids), including many popular test species. We discuss these and other issues with reproduction data, reflect on their potential impact on DEB-TKTD analysis, and provide preliminary recommendations to correct them. Both modellers and users of model results need to be aware of these complications, as ignoring them could easily lead to unnecessary failure of DEB-TKTD models during calibration, or when validating them against independent data for other exposure scenarios.

category: ecology


title: Global Gene Expression Divergence in Spontaneous Mutation Accumulation Lines of Caenorhabditis elegans under Varying Efficiency of Selection

abstract: To ascertain the effect of relaxation of selection on global gene expression, Caenorhabditis elegans mutation accumulation (MA) lines were propagated under varying degrees of efficiency of selection determined by their different population sizes (N = 1, 10 and 100). Both the mutational variance (Vm), and the residual variance (Vr) were greatest in MA lines with the lowest efficiency of natural selection. The results suggest that gene expression is under strong balancing selection. Furthermore, mutations resulting in increased transcriptional noise or sensitivity to microenvironmental variation accumulate most under extreme genetic drift. In contrast, the Vm/Vr ratio was lowest in the N =1 lines. Chromatin domains associated with broad gene silencing and active transcription exhibited the greatest and the smallest increase in transcriptional variation, respectively. Furthermore, the preponderance of overexpressed genes was especially pronounced in mitochondrial respiration, stress response, and immune system pathways, especially in low fitness N = 1 lines.

category: evolutionary biology


title: Ablation of mpeg+ macrophages exacerbates mfrp-related hyperopia

abstract:
PURPOSEProper refractive development of the eye, termed emmetropization, is critical for focused vision and impacted by both genetic determinants and several visual environment factors. Improper emmetropization caused by genetic variants can lead to congenital hyperopia, which is characterized by small eyes and relatively short ocular axial length. To date variants in only four genes have been firmly associated with human hyperopia, one of which is MFRP. Zebrafish mfrp mutants also have hyperopia and similar to reports in mice, exhibit increased macrophage recruitment to the retina. The goal of this research was to examine the effects of macrophage ablation on emmetropization and mfrp-related hyperopia.

METHODSWe utilized a chemically inducible, cell-specific ablation system to deplete macrophages in both wild-type and mfrp mutant zebrafish. Spectral-domain optical coherence tomography (SD-OCT) was used to measure components of the eye and determine relative refractive state. Histology, immunohistochemistry, and transmission electron microscopy was used to further study the eyes.

RESULTSWhile macrophage ablation does not cause significant changes to the relative refractive state of wild-type zebrafish, macrophage ablation in mfrp mutants significantly exacerbates their hyperopic phenotype.

CONCLUSIONSGenetic inactivation of mfrp leads to hyperopia as well as abnormal accumulation of macrophages in the retina. Ablation of the mpeg1-positive macrophage population exacerbates the hyperopia, suggesting that macrophages are recruited in an effort help preserve emmetropization and ameliorate hyperopia.


title: Revisiting the Hayflick Limit: Insights from an Integrated Analysis of Changing Transcripts, Proteins, Metabolites and Chromatin

abstract: The process wherein dividing cells exhaust proliferative capacity and enter into replicative senescence has become a prominent model for cellular aging in vitro. Despite decades of study, this cellular state is not fully understood in culture and even much less so during aging. Here, we revisit Leonard Hayflicks original observation of replicative senescence in WI-38 human lung fibroblasts equipped with a battery of modern techniques including RNA-seq, single cell RNA-seq, proteomics, metabolomics, and ATAC-seq. We find evidence that the transition to a senescent state manifests early, increases gradually, and corresponds to a concomitant global increase in DNA accessibility in nucleolar and lamin associated domains. Furthermore, we demonstrate that senescent WI-38 cells acquire a striking resemblance to myofibroblasts in a process similar to the epithelial to mesenchymal transition (EMT) that is regulated by the transcription factors YAP1/TEAD1 and TGF-{beta}2. Lastly, we show that verteporfin inhibition of YAP1/TEAD1 activity in aged WI-38 cells robustly attenuates this gene expression program.


title: Automation assisted anaerobic phenotyping for metabolic engineering

abstract: Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for a high-throughput, laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies - an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. Further, we propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding in conjunction with our phenotyping platform to serve as an effective scale-down model for bioreactor phenotypes. By integrating an in-house data-analysis pipeline, we were able to accelerate the  test phase of the design-build-test-learn cycle of metabolic engineering.


title: Increased alpha-helicity of a supercharged coiled-coil protein increases siRNA delivery efficiency of protein-lipid hybrid vehicle

abstract: Gene therapy has the potential to treat various diseases and has recently gained new interest due to the deployment nucleic acid based vaccines for COVID-19. Despite these developments, there still remains a need for further development of gene delivery vehicles to increase their safety and efficacy.. We have recently developed a lipoproteoplex (LPP) consisting of a super-charged coiled-coil protein (CSP) and a cationic liposomal carrier, that has the ability to condense nucleic acids and deliver them in vivo. The LPP is distinct from other liposomal gene delivery systems in that it utilizes a modular protein component to drive transfection activity as opposed to relying on the passive effects of the cationic lipids. A CSP library has been rationally designed to improve the efficacy of the LPP compared to the parent protein via improved alpha-helical structure and increased nucleic acid binding through the use of extended histidine tags and increased positive charge. The secondary structure and nucleic acid binding ability of each library member was assessed, then compared to functional transfection data in NIH-3T3 mouse fibroblasts. Structural and functional data suggests that increasing alpha-helicity of the protein component of the LPP compared to the parent sequence doubles nucleic acid binding affinity and increases transfection activity almost 3-fold with a favorable safety profile.


title: Recovering mixtures of fast diffusing states from short single particle trajectories

abstract:
Single particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we developed methods to infer distributions of diffusion coefficients from SPT data with short trajectories, variable localization accuracy, and absence of prior knowledge about the number of underlying states. We discuss advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Significance statementSingle particle tracking (SPT) uses fluorescent probes to track the motions of individual molecules inside living cells, providing biologists with a close view of the cells inner machinery at work. Commonly used SPT imaging approaches, however, result in fragmentation of trajectories into small pieces as the probes move through the microscopes plane of focus. This makes it challenging to extract usable biological information. This paper describes a method to reconstruct an SPT targets dynamic profile from these trajectory fragments. The method builds on previous approaches to provide information about challenging SPT targets without discrete dynamic states while accounting for some known biases, enabling observation of previously hidden features in mammalian SPT experiments.


title: Structural visualization of de novo initiation of RNA polymerase II transcription

abstract: Structural studies of the initiation-elongation transition of RNA polymerase II (pol II) transcription were previously facilitated by the use of synthetic oligonucleotides. Here we report structures of initiation complexes de novo converted from pre-initiation complex (PIC) through catalytic activities and stalled at different template positions. Contrary to previous models, the closed-to-open promoter transition was accompanied by a large positional change of the general transcription factor TFIIH which became in closer proximity to TFIIE for the active delivery of the downstream DNA to the pol II active center. The initially-transcribing complex (ITC) reeled over 80 base pairs of the downstream DNA by scrunching, while retaining the fixed upstream contact, and underwent the transition to elongation when it encountered promoter-proximal pol II from a preceding round of transcription. TFIIH is therefore conducive to promoter melting, TSS scanning, and promoter escape, extending far beyond synthesis of a short transcript.


title: Context-dependent effects of whole-genome duplication during mammary tumor recurrence

abstract: Whole-genome duplication (WGD) generates polyploid cells possessing more than two copies of the genome and is among the most common genetic abnormalities in cancer. The frequency of WGD increases in advanced and metastatic tumors, and WGD is associated with poor prognosis in diverse tumor types, suggesting a functional role for polyploidy in tumor progression. Experimental evidence suggests that polyploidy has both tumor-promoting and suppressing effects, but how polyploidy regulates tumor progression remains unclear. Using a genetically engineered mouse model of Her2-driven breast cancer, we explored the prevalence and consequences of whole-genome duplication during tumor growth and recurrence. While primary tumors in this model are invariably diploid, nearly 40% of recurrent tumors undergo WGD. WGD in recurrent tumors was associated with increased chromosomal instability, decreased proliferation and increased survival in stress conditions. The effects of WGD on tumor growth were dependent on tumor stage. Surprisingly, in recurrent tumor cells WGD slowed tumor formation, growth rate and opposed the process of recurrence, while WGD promoted the growth of primary tumors. These findings highlight the importance of identifying conditions that promote the growth of polyploid tumors, including the cooperating genetic mutations that allow cells to overcome the barriers to WGD tumor cell growth and proliferation.


title: Longitudinal analysis of diffuse glioma reveals cell state dynamics at recurrence associated with changes in genetics and the microenvironment

abstract: To interrogate the factors driving therapy resistance in diffuse glioma, we collected and analyzed RNA and/or DNA sequencing data from temporally separated tumor pairs of 292 adult patients with IDH-wild-type or IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions associated with an increase in proliferating stem-like malignant cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their malignant cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a specific myeloid cell state defined by unique ligand-receptor interactions with malignant cells. Collectively, our results uncover recurrence-associated changes that could be targetable to shape disease progression following initial diagnosis.


title: MLL4 is a critical mediator of differentiation and ferroptosis in the epidermis

abstract: The epigenetic regulator, MLL4 (KMT2D), has been described as an essential gene in both humans and mice1,2. In addition, it is one of the most commonly mutated genes in all of cancer biology3-7. Here, we identify a critical role for Mll4 in the promotion of epidermal differentiation and ferroptosis, a key mechanism of tumor suppression8,9. Mice lacking epidermal Mll4, but not the related enzyme Mll3 (Kmt2c), display features of impaired differentiation and human pre-cancerous neoplasms, including epidermal hyperplasia, atypical keratinocytes, and a loss of polarization, all of which progress with age. Mll4 deficiency profoundly alters epidermal gene expression, and uniquely rewires the expression of key genes and markers of ferroptosis (Alox12, Alox12b, Aloxe3)10. Beyond identifying a novel role for Mll4-mediated tumor suppression in the skin, our data reveal a potentially much more broad and general role for ferroptosis in the process of epidermal differentiation and skin homeostasis.


title: Aberrant BCMA Signaling Promotes Tumor Growth by Altering Protein Translation Machinery, a Therapeutic Target for the Treatment of Relapse/Refractory Multiple Myeloma

abstract:
Recent T Cell therapies have been effective in the treatment of hematological cancers. However, immunotoxicity and treatment relapse pose significant clinical challenges. Here, we revealed distinctive requirement for neutralizing TNF receptor ligands APRIL and BAFF in MM and DLBCL. Furthermore, we investigated the use of BCMA decoy receptor (sBCMA-Fc) as a therapeutic inhibitor of ARPIL and BAFF. While wild-type sBCMA-Fc successfully blocked APRIL signaling with picomolar binding affinity, inhibiting tumor growth in MM models, it lacked efficacy in inhibiting DLBCL progression due to its weak binding for BAFF. To expand the therapeutic utility of sBCMA-Fc, using a protein engineering approach, we generated an affinity enhanced mutant sBCMA-Fc fusion molecule (sBCMA-Fc V3) with 4-folds and 500-folds enhancement in binding to APRIL and BAFF respectively. The sBCMA-Fc V3 clone significantly enhanced antitumor activity against both MM and DLBCL. Importantly, sBCMA-Fc V3 was proven to be a viable clinical candidate by showing adequate toxicity profile and on-target mechanism of action in nonhuman primates.

SUMMARYThis study demonstrates the dichotomous function of APRIL and BAFF in MM and DLBCL, that can be safely targeted by an engineered fusion protein designed to trap APRIL and BAFF with ultra-high binding affinity.


title: Inhibition of BCMA signaling alters protein translation and Multiple Myeloma growth


title: Developing High-Affinity Decoy Receptor Optimized for Multiple Myeloma and Diffuse Large B Cell Lymphoma Treatment


title: A spatially resolved mechanistic growth law for cancer drug development.

abstract: Mathematical models used in pre-clinical drug discovery tend to be empirical growth laws. Such models are well suited to fitting the data available, mostly longitudinal studies of tumour volume, however, they typically have little connection with the underlying physiological processes. This lack of a mechanistic underpinning restricts their flexibility and inhibits their direct translation across studies including from animal to human. Here we present a mathematical model describing tumour growth for the evaluation of single agent cytotoxic compounds that is based on mechanistic principles. The model can predict spatial distributions of cell subpopulations and account for spatial drug distribution effects within tumours. Importantly, we demonstrate the model can be reduced to a growth law similar in form to the ones currently implemented in pharmaceutical drug development for pre-clinical trials so that it can integrated into the current workflow. We validate this approach for both cell-derived xenograft (CDX) and patient-derived xenograft (PDX) data. This shows that our theoretical model fits as well as the best performing and most widely used models. However, in addition the model is also able to accurately predict the observed growing fraction of tumours. Our work opens up current pre-clinical modelling studies to also incorporating spatially resolved and multi-modal data without significant added complexity and creates the opportunity to improve translation and tumour response predictions.

category: pharmacology and toxicology


title: The maize E3 ligase ZmCER9 specifically targets activated NLRs for degradation

abstract: The authors have withdrawn their manuscript whilst they perform additional experiments to test some of their conclusions further. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author

category: plant biology


title: CausER - a framework for inferring causal latent factors using multi-omic human datasets

abstract: High-dimensional cellular and molecular profiling of human samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate predictive biomarkers and prioritized causal inferences. Current methods are limited by high dimensionality of the combined datasets, the differences in their data distributions and their integration to infer causal relationships. Here we present Essential Regression (ER), an interpretable machine learning approach for high-dimensional multi-omic datasets, that addresses these problems by identifying latent factors and their likely cause-effect relationships with the system-wide outcome/properties of interest. ER is a novel data-distribution-free latent-factor regression model that integrates multi-omic datasets and identifies latent factors significantly associated with an outcome. ER outperforms a range of state-of-the-art methods in terms of prediction performance on simulated datasets. ER can be coupled with probabilistic graphical modeling thereby strengthening the causal inferences. ER generates novel cellular and molecular predictions, using multi-omic human systems immunology datasets, pertaining to immunosenescence and immune dysregulation.

category: systems biology


title: Essential Regression - a generalizable framework for inferring causal latent factors from multi-omic human datasets


title: Single-cell gene regulatory network inference atscale: The Inferelator 3.0

abstract:
MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.

ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.

AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/).


title: High performance single-cell gene regulatory network inference atscale: The Inferelator 3.0


title: High performance single-cell gene regulatory network inference at scale: The Inferelator 3.0


title: Predicting the effects of drug combinations using probabilistic matrix factorization

abstract: Drug development is costly and time-consuming, and developing novel practical strategies for creating more effective treatments is imperative. One possible solution is to prescribe drugs in combination. Synergistic drug combinations could allow lower doses of each constituent drug, reducing adverse reactions and drug resistance. However, it is not feasible to sufficiently test every combination of drugs for a given illness to determine promising synergistic combinations. Since there is a finite amount of time and resources available for finding synergistic combinations, a model that can identify synergistic combinations from a limited subset of all available combinations could accelerate development of therapeutics. By applying recommender algorithms, such as the low-rank matrix completion algorithm Probabilistic Matrix Factorization (PMF), it may be possible to identify synergistic combinations from partial information of the drug interactions. Here, we use PMF to predict the efficacy of two-drug combinations using the NCI ALMANAC, a robust collection of pairwise drug combinations of 104 FDA-approved anticancer drugs against 60 common cancer cell lines. We find that PMF is able predict drug combination efficacy with high accuracy from a limited set of combinations and is robust to changes in the individual training data. Moreover, we propose a new PMF-guided experimental design to detect all synergistic combinations without testing every combination.


title: Minian: An open-source miniscope analysis pipeline

abstract: Miniature microscopes have gained considerable traction for in vivo calcium imaging in freely behaving animals. However, extracting calcium signals from raw videos is a computationally complex problem and remains a bottleneck for many researchers utilizing single-photon in vivo calcium imaging. Despite the existence of many powerful analysis packages designed to detect and extract calcium dynamics, most have either key parameters that are hard-coded or insufficient step-by-step guidance and validations to help the users choose the best parameters. This makes it difficult to know whether the output is reliable and meets the assumptions necessary for proper analysis. Moreover, large memory demand is often a constraint for setting up these pipelines since it limits the choice of hardware to specialized computers. Given these difficulties, there is a need for a low memory demand, user-friendly tool offering interactive visualizations of how altering parameters at each step of the analysis affects data output. Our open-source analysis pipeline, Minian (Miniscope Analysis), facilitates the transparency and accessibility of single-photon calcium imaging analysis, permitting users with little computational experience to extract the location of cells and their corresponding calcium traces and deconvolved neural activities. Minian contains interactive visualization tools for every step of the analysis, as well as detailed documentation and tips on parameter exploration. Furthermore, Minian has relatively small memory demands and can be run on a laptop, making it available to labs that do not have access to specialized computational hardware. Minian has been validated to reliably and robustly extract calcium events across different brain regions and from different cell types. In practice, Minian provides an open-source calcium imaging analysis pipeline with user-friendly interactive visualizations to explore parameters and validate results.

category: neuroscience


title: Epigenetic Programming during thymic development sets the stage for optimal function in effector T cells via DNA demethylation

abstract: The repressive effect of DNA methylation at promoters is well-known. However, its role within conserved sequences in intragenic and intergenic regions is less clear. Using Cd4 as a model gene, here we show that DNA methylation regulates the function of stimulus-responsive regulatory elements in effector T cells. Two cis-elements orchestrate intra-and intergenic DNA demethylation of the Cd4 gene during thymic development, which in turn licenses a stimulus-responsive element, E4a, for its later function in effector cells. Deficiency in DNA demethylation leads to impaired E4a function, reduced H3K4me3 promoter levels and an inability to repel de novo DNA methylation during replication, ultimately leading to gene silencing. This physiological reduction in CD4 expression leads to a defect in Th1 polarization during cutaneous Leishmaniasis. Similar patterns of regulation were observed in a broad number of genes, highlighting an essential role for DNA demethylation during thymic development in modulating the function of stimulus-responsive elements.


title: Benchmark of data processing methods and machine learning models for gut microbiome-based diagnosis of inflammatory bowel disease

abstract:
BackgroundInflammatory bowel disease (IBD) patients wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiomes composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools.

ResultsWe collected fifteen 16S rRNA microbiome datasets (7707 samples) from North America to benchmark combinations of gut microbiome features, data normalization methods, batch effect reduction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with four binary classification metrics following leave-one dataset-out cross validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features obtained from QIIME2 lead to better classification of samples from IBD patients than inferred functional features obtained from PICRUSt2. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Prior to training a non-linear machine learning model on taxonomic features, it is important to apply a compositional normalization method and remove batch effects with the naive zero-centering method. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics.

ConclusionsThese findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.

category: microbiology


title: Differential regulation of developmental stages supports a linear model for C. elegans postembryonic development

abstract: The repetitive nature of C. elegans postembryonic development is considered an oscillatory process, a concept that has gained traction from regulation by a circadian clock gene homolog. Nevertheless, each larval stage has a defined duration and entails specific events. We have measured the duration of each stage of development for over 2,500 larvae, under varied environmental conditions known to alter overall developmental rate. Our results show that distinct developmental stages respond differently to environmental perturbations, including changes in temperature, in food quantity and quality, and amount of insulin signaling. Furthermore, our high-resolution measurement of the effect of temperature on the stage-specific duration of development has unveiled novel features of temperature dependence in C. elegans postembryonic development. Altogether, our results support a model of linear progression of C. elegans development, with the duration of each stage determined by a unique program.