DeLUCS: Deep Learning for Unsupervised Clustering of DNA Sequences We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets.
Gene expression and DNA methylation consistently predict cancer mutation states In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts.

Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. Surprisingly, we found that for many of the genes we considered, one or more other data types are approximately equally effective predictors. Performance was more variable between mutations than it was between data types for the same mutation, and there was often little difference between the top data types. We also found that combining data types into a single multi-omics model provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
F1F0 ATP Hydrolysis is a Determinant of Metabolic Rate, a Correlate of Lifespan, and a Weakness of Cancer Dramatic rectal temperature decrease, in mice administered with a drug that specifically inhibits F1F0 ATP hydrolysis, suggests that F1F0 ATP hydrolysis is a major determinant of metabolic rate in vivo. Across twelve investigated species, less F1F0 ATP hydrolysis correlates with greater maximal lifespan. Specific drug inhibition of F1F0 ATP hydrolysis exerts potent anti-cancer activity in vitro. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. The cyclic dinucleotide 2'3'-cGAMP induces a broad anti-bacterial and anti-viral response in the sea anemone Nematostella vectensis In mammals, cyclic dinucleotides (CDNs) bind and activate STING to initiate an anti-viral type I interferon response. CDNs and STING originated in bacteria and are present in most animals. By contrast, interferons are believed to have emerged in vertebrates; thus, the function of CDN signaling in invertebrates is unclear. Here, we use a CDN, 23-cGAMP, to activate immune responses in a model cnidarian invertebrate, the starlet sea anemone Nematostella vectensis. Using RNA-Seq, we found that 23-cGAMP induces robust transcription of both anti-viral and anti-bacterial genes in N. vectensis. Many of the anti-viral genes induced by 23-cGAMP are homologs of vertebrate interferon stimulated genes, implying that the interferon response predates the evolution of interferons. Knockdown experiments identified a role for NF-{kappa}B in specifically inducing anti-bacterial genes downstream of 23-cGAMP. Some of these putative anti-bacterial genes were also found to be induced during Pseudomonas aeruginosa infection. We characterized the protein product of one of the putative anti-bacterial genes, the N. vectensis homolog of Dae4, and found that it has conserved anti-bacterial activity. This work suggests that a broad anti-bacterial and anti-viral transcriptional response is an evolutionarily ancestral output of 23-cGAMP signaling in animals.

Significance statementCyclic dinucleotides are signaling molecules that originated in bacteria and were subsequently acquired and co-opted by animals for immune signaling. The major cyclic dinucleotide signaling pathway in mammals results in the production of anti-viral molecules called interferons. Invertebrates such as sea anemones lack interferons, and thus it was unclear whether cyclic dinucleotide signaling would play a role in immunity in these animals. Here we report that in the anemone Nematostella vectensis, cyclic dinucleotides activate both anti-viral and anti-bacterial immune responses, and do so through a conserved pathway. These results provide insights into the evolutionary origins of innate immunity, and suggest a broader ancestral role for cyclic dinucleotide signaling that evolved toward more specialized anti-viral functions in mammals. NPEPPS regulates intracellular import and sensitivity to cisplatin by interaction with volume regulated anion channels Despite routine use of platinum-based chemotherapeutics in cancer treatment, there remains a need to improve efficacy and patient selection. Multi-omic assessment of human bladder cancer cell lines and their cisplatin resistant derivatives and whole-genome CRISPR screens identified NPEPPS, the puromycin-sensitive aminopeptidase as a novel driver of cisplatin resistance. NPEPPS depletion increased cisplatin import and sensitization of resistant cells in vitro and in vivo. Pharmacologic inhibition of NPEPPS in cells and chemoresistant, patient-derived tumor organoids improved response to cisplatin. NPEPPS was found in complex with volume regulated anion channel (VRAC) subunits LRRC8A and LRRC8D, whose loss is known to enhance resistance to cisplatin. Depletion of LRRC8A the only obligate subunit for normal VRAC function abrogated the effect of NPEPPS-mediated cisplatin import. Our findings describe the first mechanism by which VRACs can be targeted for therapeutic benefit.

HIGHLIGHTSO_LIMulti-omic screening found NPEPPS is a driver of cisplatin resistance in cancer
C_LIO_LINPEPPS is in protein complex with LRRC8A and D, volume regulated anion channel (VRAC) subunits
C_LIO_LILRRC8A and D loss increases cisplatin resistance and reduce its intracellular levels
C_LIO_LINPEPPS regulates cisplatin import and sensitivity through VRACs
C_LIO_LINPEPPS function is inhibited by small molecules offering potential for clinical translation
C_LI Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Resolving when (and where) the Thylacine went extinct Like the Dodo and Passenger Pigeon before it, the predatory marsupial Thylacine (Thylacinus cynocephalus), or  Tasmanian tiger, has become an iconic symbol of human-caused extinction. The last captive animal died in 1936, but even today reports of the Thylacines possible ongoing survival in remote regions of Tasmania are newsworthy and capture the publics imagination. Extirpated from mainland Australia in the mid-Holocene, the large island of Tasmania became the species final stronghold. Following European settlement in the 1800s, the Thylacine was heavily persecuted and pushed to the margins of its range, although many sightings were reported thereafter--even well beyond the 1930s. To gain a new depth of insight into the extinction of the Thylacine, we assembled an exhaustive database of 1,237 observational records from Tasmania (from 1910 onwards), quantified their uncertainty, and charted the patterns these revealed. We also developed a new method to visualize the species 20th-century spatio-temporal dynamics, to map potential post-bounty refugia and pinpoint the most-likely location of the final persisting subpopulation. A direct reading of the high-quality records (confirmed kills and captures, in combination with sightings by past Thylacine hunters and trappers, wildlife professionals and experienced bushmen) implies a most-likely extinction date within four decades following the last capture (i.e., 1940s to 1970s). However, uncertainty modelling of the entire sighting record, where each observation is assigned a probability and the whole dataset is then subject to a sensitivity analysis, suggests that extinction might have been as recent as the late 1980s to early 2000s, with a small chance of persistence in the remote south-western wilderness areas. Beyond the intrinsically fascinating problem of reconstructing the final fate of the Thylacine, the new spatio-temporal mapping of extirpation developed herein would also be useful for conservation prioritization and search efforts for other rare taxa of uncertain status. Electrical Stimulated GLUT4 Signaling Attenuates Critical Illness-Associated Muscle Wasting BackgroundCritical illness myopathy (CIM) is a debilitating condition characterized by the preferential loss of the motor protein myosin. CIM is a byproduct of critical care, attributed to impaired recovery, long-term complications, and mortality. CIM pathophysiology is complex, heterogeneous and remains incompletely understood, however loss of mechanical stimuli contributes to critical illness associated muscle atrophy and weakness. Passive mechanical loading (ML) and electrical stimulation (ES) therapies augment muscle mass and function. While having beneficial outcomes, the mechanistic underpinning of these therapies is less known. Therefore, here we aimed to assess the mechanism by which chronic supramaximal ES ameliorates CIM in a unique experimental rat model of critical care.

MethodsRats were subjected to 8 days critical care conditions entailing deep sedation, controlled mechanical ventilation, and immobilization with and without direct soleus ES. Muscle size and function were assessed at the single cell level. RNAseq and Western blotting were employed to understand the mechanisms driving ES muscle outcomes in CIM.

ResultsFollowing 8 days of controlled mechanical ventilation and immobilization, soleus muscle mass, Myosin:Actin ratio and single muscle fiber maximum force normalized to cross-sectional area (specific force) were reduced by 40-50% (p< 0.0001). ES significantly reduced the loss of soleus muscle fiber cross-sectional area (CSA) and Myosin:Actin ratio by approximately 30% (p< 0.05) yet failed to effect specific force. RNAseq pathway analysis revealed downregulation of insulin signaling in the soleus muscle following critical care and GLUT4 trafficking was reduced by 55% leading to an 85% reduction of muscle glycogen content (p< 0.01). ES promoted phosphofructokinase and insulin signaling pathways to control levels (p< 0.05), consistent with the maintenance of GLUT4 translocation and glycogen levels. AMPK, but not AKT, signaling pathway was stimulated following ES, where the downstream target TBC1D4 increased 3 logFC (p= 0.029) and AMPK-specific P-TBC1D4 levels were increased approximately 2-fold (p= 0.06). Reduction of muscle protein degradation rather than protein synthesis promoted soleus CSA, as ES reduced E3 ubiquitin proteins, Atrogin-1 (p= 0.006) and MuRF1 (p= 0.08) by approximately 50%, downstream of AMPK-FoxO3.

ConclusionsES maintained GLUT4 translocation through increased AMPK-TBC1D4 signaling leading to improved muscle glucose homeostasis. Soleus CSA and myosin content was promoted through reduced protein degradation via AMPK-FoxO3 E3 ligases, Atrogin-1 and MuRF1. These results demonstrate chronic supramaximal ES reduces critical care associated muscle wasting, preserved glucose signaling and reduced muscle protein degradation in CIM. Teosinte mexicana introgression modulates phosphatidylcholine levels and maize flowering time Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp.parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability, and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern US, Canada and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Echolocation reverses information flow in a cortical vocalization network The mammalian frontal and auditory cortices are important for vocal behaviour. Here, using local field potential recordings, we demonstrate for the first time that the timing and spatial pattern of oscillations in the fronto-auditory cortical network of vocalizing bats (Carollia perspicillata) predict the purpose of vocalization: echolocation or communication. Transfer entropy analyses revealed predominantly top-down (frontal-to-auditory cortex) information flow during spontaneous activity and pre-vocal periods. The dynamics of information flow depended on the behavioural role of the vocalization and on the timing relative to vocal onset. Remarkably, we observed the emergence of predominantly bottom-up (auditory-to-frontal cortex) information transfer patterns specific echolocation production, leading to self-directed acoustic feedback. Electrical stimulation of frontal areas selectively enhanced responses to echolocation sounds in auditory cortex. These results reveal unique changes in information flow across sensory and frontal cortices, potentially driven by the purpose of the vocalization in a highly vocal mammalian model. Honeycomb crystallography: comb formation under geometric frustrations 1As honeybees build their nests in pre-existing tree cavities, they must deal with dealing with the presence of geometric constraints, resulting in non-regular hexagons and topological defects in the comb. In this work, we study how bees adapt to their environment in order to regulate the comb structure. Specifically, we identify the irregularities in honeycomb structure in the presence of various geometric frustrations. We 3D-print experimental frames with a variety of constraints imposed on the imprinted foundations. The combs constructed by the bees show clear evidence of reoccurring patterns built by bees in response to specific geometric frustrations on these starter frames. Furthermore, using an experimental-modeling framework, we demonstrate that these patterns can be successfully modeled and replicated through a simulated annealing process, in which the minimized potential is a variation of the Lennard-Jones potential that only considers first-neighbor interactions according to a Delaunay triangulation. Our simulation results not only confirm the connection between honeycomb structures and other crystal systems such as graphene, but also show that irregularities in the honeycomb structure can be explained as the result of local interactions between honeybees and their immediate surroundings, leading to emergent global order. Additionally, our computational model can be used to describe specific strategies that bees use to effectively solve each geometric mismatch problem while minimizing cost of comb building. Meiotic DSB-independent role of protein phosphatase 4 in Hop1 assembly to promote meiotic chromosome axis formation in budding yeast Dynamic changes in chromosomal structure that occur during meiotic prophase play an important role in the progression of meiosis. Among these structures, meiosis-specific chromosomal axis-loop structures are important as a scaffold for integrated control between the meiotic recombination reaction and the associated checkpoint system to ensure accurate chromosome segregation. However, the molecular mechanism of the initial step of chromosome axis-loop construction is not well understood. Here, we showed that in budding yeast, protein phosphatase 4 (PP4) that primarily counteracts Mec1/Tel1 phosphorylation is required to promote the assembly of chromosomal axis components Hop1 and Red1 onto meiotic chromatin via interaction with Hop1. PP4, in contrast, did not affect Rec8 assembly. Notably, unlike the previously known function of PP4, this novel function of PP4 was independent of meiotic DSB-dependent Tel1/Mec1 kinase activities. The defect in Hop1/Red1 assembly in the absence of PP4 function was not suppressed by dysfunction of Pch2, which removes Hop1 protein from the chromosome axis. This suggests that PP4 is required for the initial step of chromatin loading of Hop1 rather than stabilization of Hop1 on axes. These results indicate that phosphorylation/dephosphorylation-mediated regulation of Hop1 recruitment onto chromatin occurs during chromosome axis construction before meiotic double-strand break formation. An isogenic collection of pluripotent stem cell lines with elevated α-synuclein expression -Synuclein (Syn) is a small, disordered protein that becomes aggregated in Lewy body diseases, such as Parkinsons disease (PD) and dementia with Lewy bodies (DLB). Human induced pluripotent stem cells (hiPSCs) potentially provide a tractable disease model to monitor early molecular changes associated with PD/DLB. We and others have previously derived hiPSC lines from patients with duplication and triplication of the SNCA gene, encoding for Syn. It is now recognised that to perform meaningful disease modelling with these hiPSC lines, it is critical to generate isogenic control cell lines that lack the disease causing mutations. In order to complement the existing and emerging hiPSC models for PD/DLB, we have generated an allelic series of Syn over-expressing hESC lines on the same isogenic background. An unresolved question is whether pluripotent stem cell lines, with elevated levels of Syn, can undergo efficient differentiation into dopaminergic and cortical neurons to model PD and DLB, respectively. We took advantage of our isogenic collection of hESC lines to determine if increased expression of Syn affects neural induction and neuronal differentiation. Clonal hESC lines with significantly different levels of Syn expression proliferated normally and maintained expression of pluripotent markers, such as OCT4. All cell lines efficiently produced PAX6+ neuroectoderm and there was no correlation between Syn expression and neural induction efficiency. Finally, global transcriptomic analysis of cortical differentiation of hESC lines with low or high levels of Syn expression demonstrated robust and similar induction of cortical neuronal expression profiles. Gene expression differences observed were unrelated to neural induction and neuronal differentiation. We conclude that elevated expression of Syn in human pluripotent stem cells does not adversely affect their neuronal differentiation potential and that collections of isogenic cell lines with differing levels of Syn expression are valid and suitable models to investigate synucleinopathies. PLB-985 neutrophil-like cells as a model to study Aspergillus fumigatus pathogenesis Fungal infections remain a major global concern. Emerging fungal pathogens and increasing rates of resistance mean that additional research efforts and resources must be allocated to advancing our understanding of fungal pathogenesis and developing new therapeutic interventions. Neutrophilic granulocytes are a major cell type involved in protection against the important fungal pathogen Aspergillus fumigatus, where they employ numerous defense mechanisms, including production of antimicrobial extracellular vesicles. A major draw-back to work with neutrophils is the lack of a suitable cell line system for the study of fungal pathogenesis. To address this problem, we assessed the feasibility of using differentiated PLB-985 neutrophil-like cells as an in vitro model to study A. fumigatus infection. We find that dimethylformamide-differentiated PLB-985 cells provide a useful recapitulation of many aspects of A. fumigatus interactions with primary human polymorphonuclear leukocytes. We show that differentiated PLB-985 cells phagocytose fungal conidia and acidify conidia-containing phagolysosomes similar to primary neutrophils, release neutrophil extracellular traps, and also produce antifungal extracellular vesicles in response to infection. In addition, we provide an improved method for the isolation of extracellular vesicles produced during infection by employing a size-exclusion chromatography-based approach. Advanced LC-MS/MS proteomics revealed an enrichment of extracellular vesicle marker proteins and a decrease of cytoplasmic proteins in extracellular vesicles isolated using this improved method. Ultimately, we find that differentiated PLB-985 cells can serve as a genetically tractable model to study many aspects of A. fumigatus pathogenesis.

IMPORTANCEPolymorphonuclear leukocytes are an important defense against human fungal pathogens, yet our model systems to study this group of cells remains very limited in scope. In this study, we established that differentiated PLB-985 cells can serve as a model to recapitulate several important aspects of human polymorphonuclear leukocyte interactions with the important human fungal pathogen Aspergillus fumigatus. The proposed addition of a cultured neutrophil-like cell line to the experimental toolbox to study fungal pathogenesis will allow for a more mechanistic description of neutrophil antifungal biology. In addition, the easier handling of the cell line compared to primary human neutrophils allowed us to use PLB-985 cells to provide an improved method for isolation of neutrophil-derived extracellular vesicles using size-exclusion chromatography. Together, these results provide significant tools and a baseline knowledge for the future study of neutrophil-derived extracellular vesicles in the laboratory. Sequence features of retrotransposons allow for epigenetic variability Transposable elements (TEs) are mobile genetic elements that make up a large fraction of mammalian genomes. While select TEs have been co-opted in host genomes to have function, the majority of these elements are epigenetically silenced by DNA methylation in somatic cells. However, some TEs in mice, including the Intracisternal A-particle (IAP) subfamily of retrotransposons, have been shown to display interindividual variation in DNA methylation. Recent work has revealed that IAP sequence differences and strain-specific KRAB zinc finger proteins (KZFPs) may influence the methylation state of these IAPs. However, the mechanisms underlying the establishment and maintenance of interindividual variability in DNA methylation still remain unclear. Here we report that sequence content and genomic context influence the likelihood that IAPs become variably methylated. IAPs that differ from consensus IAP sequences have altered KZFP recruitment that can lead to decreased KAP1 recruitment when in proximity of constitutively expressed genes. These variably methylated loci have a high CpG density, similar to CpG islands, and can be bound by ZF-CxxC proteins, providing a potential mechanism to maintain this permissive chromatin environment and protect from DNA methylation. These observations indicate that variably methylated IAPs escape silencing through both attenuation of KZFP binding and recognition by ZF-CxxC proteins to maintain a hypomethylated state. Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics Data There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

Author summaryReconstruction of multiple association networks from high dimensional omics data is an important topic, especially in biology. Previous studies focused on estimating different networks and detecting common hubs among all classes. Integration of information over different classes of data while allowing difference in the hub nodes is also biologically plausible. Therefore, we propose a method, EDOHA, to jointly construct multiple interaction networks with capacity in finding different hub networks for each class of data. Simulation studies show the better performance over conventional methods. The method has been demonstrated in three real world data. Improved AlphaFold modeling with implicit experimental information Machine learning prediction algorithms such as AlphaFold1 and RoseTTAFold2 can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy3-6. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation. Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC array A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enabling directional sensitivity and scalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting. Wrinkle force microscopy: a new machine learning based approach to predict cell mechanics from images Combining experiments with artificial intelligence algorithms, we propose a new machine learning based approach to extract the cellular force distributions from the microscope images. The full process can be divided into three steps. First, we culture the cells on a special substrate allowing to measure both the cellular traction force on the substrate and the corresponding substrate wrinkles simultaneously. The cellular forces are obtained using the traction force microscopy (TFM), at the same time that cell-generated contractile forces wrinkle their underlying substrate. Second, the wrinkle positions are extracted from the microscope images. Third, we train the machine learning system with GAN (generative adversarial network) by using sets of corresponding two images, the traction field and the input images (raw microscope images or extracted wrinkle images), as the training data. The network understands the way to convert the input images of the substrate wrinkles to the traction distribution from the training. After sufficient training, the network is utilized to predict the cellular forces just from the input images. Our system provides a powerful tool to evaluate the cellular forces efficiently because the forces can be predicted just by observing the cells under the microscope, which is a way simpler method compared to the TFM experiment. Additionally, the machine learning based approach presented here has the profound potential for being applied to diverse cellular assays for studying mechanobiology of cells.

Significance StatementCell-generated forces are indispensable determinants of fundamental cell functions such as motility and cell division. As such, quantifying how the forces change upon perturbations to the cells such as gene mutations and drug administration is of profound importance. Here we present a novel machine learning based system that allows for efficient estimations of the forces that are determined only by "observing" microscope images. Given that the cellular traction forces are regulated downstream of diverse signaling pathways, our system - that helps significantly improve the throughput of the measurements - presents a new, high throughput platform for real time analysis of the effects of a massive number of genetic and molecular perturbations on the forces and resulting cell mechanics. Changes to the mtDNA copy number during yeast culture growth We show that the mtDNA copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest ([~]10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains, but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype. TRIM28-dependent SUMOylation protects the adult ovary from the testicular pathway Gonadal sexual fate in mammals is determined during embryonic development and must be actively maintained in adulthood. In the mouse ovary, oestrogen receptors and FOXL2 protect ovarian granulosa cells from transdifferentiation into Sertoli cells, their testicular counterpart. However, the mechanism underlying their protective effect is unknown. Here, we show that TRIM28 is required to prevent female-to-male sex reversal of the mouse ovary after birth. We found that upon loss of Trim28, ovarian granulosa cells transdifferentiate to Sertoli cells through an intermediate cell type, different from gonadal embryonic progenitors. TRIM28 is recruited on chromatin in the proximity of FOXL2 to maintain the ovarian pathway and to repress testicular-specific genes. The role of TRIM28 in ovarian maintenance depends on its E3-SUMO ligase activity that regulates the sex-specific SUMOylation profile of ovarian-specific genes. Our study identifies TRIM28 as a key factor in protecting the adult ovary from the testicular pathway. An Evolutionary Process Without Variation and Selection Natural selection successfully explains how organisms accumulate adaptive change despite that traits acquired over a lifetime are eliminated at the end of each generation. However, in some domains that exhibit cumulative, adaptive change--e.g., cultural evolution, and earliest life--acquired traits are retained; these domains do not face the problem that Darwins theory was designed to solve. Lack of transmission of acquired traits occurs when germ cells are protected from environmental change, due to a self-assembly code used in two distinct ways: (i) actively interpreted during development to generate a soma, and (ii) passively copied without interpretation during reproduction to generate germ cells. Early life and cultural evolution appear not to involve a self-assembly code used in these two ways. We suggest that cumulative, adaptive change in these domains is due to a lower-fidelity evolutionary process, and model it using Reflexively Autocatalytic and Foodset-generated networks. We refer to this more primitive evolutionary process as Self-Other Reorganisation (SOR) because it involves internal self-organising and self-maintaining processes within entities, as well as interaction between entities. SOR encompasses learning but in general operates across groups. We discuss the relationship between SOR and Lamarckism, and illustrate a special case of SOR without variation. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Honeybee cognition as a tool for scientific engagement In addition to the crowdsourcing of experimental data, citizen science, and scientific engagement more broadly, serve as a bridge between researchers and the wider community. This serves to foster a greater understanding of the scientific method and science-based solutions generally. Apis mellifera (honeybees) are a well-established model for the study of learning and cognition and can serve as an engaging outreach system for this wider community. Here, we developed and implemented a protocol using well established honeybee conditioning protocols to safely study the effects of caffeine and dopamine on learning performance. Using this protocol, a group of high-school aged students as part of the Ryukyu Girls program demonstrated that caffeine, but not dopamine, significantly reduced the number of trials required for a successful conditioning response. This allowed these students to explore the scientific method in a relatable and engaging way.

Simple SummaryGlobal scientific literacy can be improved through widespread and effective community engagement by researchers. We propose Apis mellifera (honeybee) as an public engagement tool due to widespread awareness of colony collapse and the bees importance in food production. Moreover, their cognitive abilities make for engaging experiments. Their relative ease of cultivation means that studies can be performed cost-effectively, especially when partnering with local aperists. Using a proxy for honeybee learning, a group of non-specialist high-school-aged participants obtained data suggesting that caffeine, but not dopamine, improved learning. This hands-on experience facilitated student understanding of the scientific method, factors that shape learning and the importance of learning for hive health.