title: Forest wildflowers bloom earlier as Europe warms - but not everywhere equally.

abstract: Some of the most striking biological responses to climate change are the observed shifts in the timing of life-history events of many organisms. Plants, in particular, often flower earlier in response to climate warming, and herbarium specimens are excellent witnesses of such long-term changes. However, in large-scale analyses the magnitude of phenological shifts may vary geographically, and the data are often clustered, and it is thus necessary to account for spatial correlation to avoid geographical biases and pseudoreplication. Here, we analysed herbarium specimens of 20 spring-flowering forest understory herbs to estimate how their flowering phenology shifted across Europe during the last century. Our analyses show that on average these forest wildflowers now bloom over six days earlier than at the beginning of the last century. These changes were strongly associated with warmer spring temperatures. Plants flowered on average of 3.6 days earlier per 1{degrees}C warming. However, in some parts of Europe plants flowered earlier or later than expected. This means, there was significant residual spatial variation in flowering time across Europe, even after accounting for the effects of temperature, precipitation, elevation and year. Including this spatial autocorrelation into our statistical models significantly improved model fit and reduced bias in coefficient estimates. Our study indicates that forest wildflowers in Europe strongly advanced their phenology in response to climate change during the last century, with potential severe consequences for their associated ecological communities. It also demonstrates the power of combining herbarium data with spatial modelling when testing for long-term phenology trends across large spatial scales.


title: Unearthing modes of climatic adaptation in underground storage organs across Liliales

abstract: Testing adaptive hypotheses about how continuous traits evolve in association with developmentally-structured discrete traits, while accounting for the confounding influence of other, hidden, evolutionary forces, remains a challenge in evolutionary biology. In one example of this, geophytes are herbaceous plants capable of retreating underground and use underground storage organs (USOs) to survive extended periods of unfavorable conditions. Such plants have evolved multiple times independently across all major vascular plant lineages. Even within closely related lineages, however, geophytes show impressive variation in the morphological modifications and structures (i.e., "types" of USOs) that allow them to survive underground. Despite the developmental and structural complexity of USOs, the prevailing hypothesis is that they represent convergent evolutionary "solutions" to a common ecological problem, though some recent research has drawn this into question. We extend existing phylogenetic comparative methods to test for links between geophytes hierarchical discrete morphological traits associated with USOs and adaptation to environmental variables, using a phylogeny of 621 species in Liliales. We found that plants with different USO type do not differ in climatic niche more than expected by chance, with the exception of root morphology, where modified roots are associated with lower temperature seasonality. These findings suggest that root tubers may reflect adaptations to different climatic conditions than those represented by other types of USOs. Thus, the tissue type and developmental origin of the USO structure may influence the way it mediates ecological relationships, which draws into question the appropriateness of ascribing broad ecological patterns uniformly across geophytic taxa. This work provides a new framework for testing adaptive hypotheses and for linking ecological patterns across morphologically varying taxa while accounting for developmental (non-independent) relationships in morphological data. [Macroevolution, geophytes, climatic niche evolution, adaptation]

category: evolutionary biology


title: Transcriptome phylogenies support ancient evolutionary transitions in bioluminescence traits of cypridinid ostracods

abstract: Although the the diversity, beauty, and intricacy of sexually selected courtship displays command the attention of evolutionists, the longevity of these traits in deep time is poorly understood. Population-based theory suggests sexual selection could either lower or raise extinction risk, resulting in high or low persistence of lineages with sexually selected traits. Furthermore, empirical studies that directly estimate longevity of sexually selected traits are uncommon. Sexually selected signals - including bioluminescent courtship - originated multiple times during evolution, allowing empirical study of their longevity after careful phylogenetic and divergence time analyses. Here, we estimate the first transcriptome-based molecular phylogeny and divergence times of Cypridinidae. We report extreme longevity of bioluminescent courtship, a trait important in mate choice and probably under sexual selection. Our relaxed-clock estimates of divergence times coupled with stochastic character mapping show luminous courtship evolved only once in Cypridinidae in a Sub-Tribe we name Luxorina at least 151 Million Years Ago (Ma) from cypridinid ancestors that used bioluminescence only in anti-predator displays, defining a Tribe we name Luminini. This time-calibrated molecular phylogeny of cypridinids will serve as a foundation for integrative and comparative studies on the biochemistry, molecular evolution, courtship, diversification, and ecology of cypridinid bioluminescence. The persistence of luminous courtship for hundreds of millions of years indicates that rates of speciation within the group exceeded extinction risk, allowing for the persistence of a diverse clade of signalling species and that sexual selection did not cause rapid loss of associated traits.


title: Sexual signals persist over deep time: ancient co-option of bioluminescence for courtship displays in cypridinid ostracods


title: Experimental evolution of insect resistance to two pesticide classes reveals mechanistic diversity and context-dependent fitness costs

abstract: Does rapid adaptation to stressors evolve through similar underlying mechanisms among diverse populations, or are there many roads to a similar phenotype? The experimental evolution of pesticide resistance in insects provides a powerful model to study the diverse evolutionary signatures of adaptation and their associated costs. Here, we selected for resistance to two pesticides (organophosphates and pyrethroids) in six field-derived populations of the red flour beetle (Tribolium castaneum). After several generations of selection, we performed transcriptomic analyses and measured survival, development, and fecundity in the presence and absence of pesticides to detect fitness costs of resistance evolution. All pesticide-selected populations exhibited significantly improved survival after pesticide exposure without substantial fitness costs, compared to control populations. Populations that evolved to resist organophosphates had distinct gene expression in the presence and absence of organophosphates, supporting different detoxification mechanisms and cuticular modifications among populations. In contrast, pyrethroid resistant populations demonstrated common differential expression of cytochrome P450 transcripts. Furthermore, some populations evolved similar mechanisms against both pesticides while others showed little overlap in their evolved responses, suggesting variation in potential cross-resistance phenotypes. Overall, between populations, we observed both parallel and divergent patterns in gene expression associated with acquired pesticide resistance, without ubiquitous fitness costs.


title: Novel classes and evolutionary turnover of histone H2B variants in the mammalian germline

abstract: Histones and their post-translational modifications facilitate diverse chromatin functions in eukaryotes. Core histones (H2A, H2B, H3, and H4) package genomes after DNA replication. In contrast, variant histones promote specialized chromatin functions, including DNA repair, genome stability, and epigenetic inheritance. Previous studies have identified only a few H2B variants in animals; their roles and evolutionary origins remain largely unknown. Here, using phylogenomic analyses, we reveal the presence of five H2B variants broadly present in mammalian genomes. In addition to three previously described variants (H2B.1, subH2B, and H2B.W), we identify and describe two new variants, H2B.L and H2B.N. Four of these five H2B variants originated in mammals, whereas H2B.L arose prior to the last common ancestor of bony vertebrates. We find that though mammalian H2B variants are subject to high gene turnover, most are broadly retained in mammals, including humans. Despite an overall signature of purifying selection, H2B variants evolve more rapidly than core H2B with considerable divergence in sequence and length. All five H2B variants are expressed in the germline. H2B.L and H2B.N are predominantly expressed in oocytes, an atypical expression site for mammalian histone variants. Our findings suggest that H2B variants likely encode potentially redundant but vital functions via unusual chromatin packaging or non-chromatin functions in mammalian germline cells. Our discovery of novel histone variants highlights the advantages of comprehensive phylogenomic analyses and provides unique opportunities to study how innovations in chromatin function evolve.


title: The genetics of eating behaviors: research in the age of COVID-19

abstract: How much pleasure we take in eating is more than just how much we enjoy the taste of food. Food involvement - the amount of time we spend on food beyond the immediate act of eating and tasting - is key to the human food experience. We took a biological approach to test whether food-related behaviors, together capturing food involvement, have genetic components and are partly due to inherited variation. We collected data via an internet survey from a genetically informative sample of 419 adult twins (114 monozygotic twin pairs, 31 dizygotic twin pairs, and 129 singletons). Because we conducted this research during the pandemic, we also ascertained how many participants had experienced COVID-19-associated loss of taste and smell. Since these respondents had previously participated in research in person, we measured their level of engagement to evaluate the quality of their online responses. Additive genetics explained 16-44% of the variation in some measures of food involvement, most prominently various aspects of cooking, suggesting some features of the human food experience may be inborn. Other features reflected shared (early) environment, captured by respondents twin status. About 6% of participants had a history of COVID-19 infection, many with transitory taste and smell loss, but all but one had recovered before the survey. Overall, these results suggest that people may have inborn as well as learned variations in their involvement with food. We also learned to adapt to research during a pandemic by considering COVID-19 status and measuring engagement in online studies of human eating behavior.

category: genetics


title: PGP1 personal genome assembly - a hybrid assembly dataset using ONT's PromethION and PacBio's HiFi sequencing

abstract: PGP1 is the first participant of Personal Genome Project. We present the PGP1s chromosome-scale genome assembly. It was constructed using 255 Gb ultra-long PromethION reads and 97 Gb short paired-end reads. For reducing base calling errors, we corrected PromethION reads using 72 Gb PacBio HiFi reads. 327 Gb Hi-C chromosomal mapping data were utilized to maximize the assemblys contiguity. PGP1s contig assembly was 3.01 Gb in length comprising of 4,234 contigs with an N50 value of 33.8 Mb. After scaffolding with Hi-C data and extensive manual curation, we obtained a chromosome-scale assembly that represents 3,880 scaffolds with an N50 value of 142 Mb. From the Merqury assessment, PGP1 assembly achieved a high QV score of Q45.45. For a gene annotation, we predicted 106,789 genes with a liftover from the Gencode 38 and an assembly of transcriptome data.

category: genomics


title: Free spermidine evokes superoxide radicals that manifest toxicity

abstract: Spermidine and other polyamines alleviate oxidative stress, yet excess spermidine seems toxic to Escherichia coli unless it is neutralized by SpeG, an enzyme for the spermidine N-acetyl transferase function. Besides, a specific mechanism of SpeG function conferring pathogenic fitness to Staphylococcus aureus USA300 strain is unknown. Here, we provide evidence that although spermidine mitigates oxidative stress by lowering hydroxyl radical and hydrogen peroxide levels, excess of it simultaneously triggers the production of superoxide radicals, thereby causing toxicity in the E. coli {Delta}speG strain as well as naturally SpeG-deficient S. aureus RN4220 strain. However, wild-type E. coli and S. aureus USA300 with a horizontally-acquired speG gene tolerate applied exogenous spermidine stress. Furthermore, we demonstrate that while RNA-bound spermidine inhibits iron oxidation, free spermidine interacts and oxidizes the iron to evoke superoxide radicals directly. Superoxide radicals thus generated, further affects redox balance and iron homeostasis. Since iron acquisition and metabolism in the host tissues is a challenging task for S. aureus, the current findings helped us explain that the evolutionary gain of SpeG function by S. aureus USA300 strain allows it to neutralize exogenous spermidine- and spermine-mediated toxicity towards iron metabolism inside the host tissues.

category: biochemistry


title: Highly specific chimeric DNA-RNA guided genome editing with enhanced CRISPR-Cas12a system

abstract: The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas12a system is composed of a Cas12a effector that acts as a deoxyribonucleic acid (DNA)-cleaving endonuclease and a crispr ribonucleic acid (crRNA) that guides the effector to the target DNA. It is considered a key molecule for inducing target-specific gene editing in various living systems. Here, we improved the efficiency and specificity of the CRISPR-Cas12a system through protein and crRNA engineering. In particular, to optimize the CRISPR-Cas12a system at the molecular level, we used a chimeric DNA-RNA guide chemically similar to crRNA to maximize target sequence specificity. Compared to the wild type (wt)-Cas12a system, when using enhanced Cas12a system (en-Cas12a), the efficiency and target specificity improved on average by 7.41 and 7.60 times respectively. In our study, when the chimeric DNA-RNA guided en-Cas12a effector was used, the gene editing efficiency and accuracy were simultaneously increased. These findings could contribute to highly accurate genome editing, such as human gene therapy, in the near future.


title: HyperEx: A Tool to Extract Hypervariable Regions from 16S rRNA Sequencing Data

abstract: The 16S ribosomal RNA gene is one of the most studied genes in biology. This 16S ribosomal RNA importance is due to its wide application in phylogenetics and taxonomic elucidation of bacteria and archaea. Indeed, 16S ribosomal RNA is present in almost all bacteria and archaea and has, among many other useful characteristics, a low mutation rate. The 16S ribosomal RNA is composed of nine hypervariable regions which are commonly targeted by high throughput sequencing technologies in identification or community studies like metabarcoding studies. Unfortunately, the hypervariable regions do not have the same taxonomic resolution among all bacteria taxa. This requires a preliminary in silico analysis to determine the best hypervariable regions to target in a particular study. Nevertheless, to the best of our knowledge, no automated primer-based open-source tool exists to extract hypervariable regions from complete or near-complete 16S rRNA sequencing data. Here we present HyperEx which efficiently extracts the hypervariable region of interest based on embedded primers or user-given primers. HyperEx implements the Myers algorithm for the exact pairwise sequence alignment. HyperEx is freely available under the MIT license as an operating system independent Rust command-line tool at https://github.com/Ebedthan/hyperex and https://crates.io.

category: bioinformatics


title: Protein embeddings and deep learning predict binding residues for various ligand classes

abstract: One important aspect of protein function is the binding of proteins to ligands, including small molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of experimental progress many binding sites remain obscure. Here, we proposed bindEmbed21, a method predicting whether a protein residue binds to metal ions, nucleic acids, or small molecules. The Artificial Intelligence (AI)-based method exclusively uses embeddings from the Transformer-based protein Language Model (pLM) ProtT5 as input. Using only single sequences without creating multiple sequence alignments (MSAs), bindEmbed21DL outperformed MSA-based predictions. Combination with homology-based inference increased performance to F1=48{+/-}3% (95% CI) and MCC=0.46{+/-}0.04 when merging all three ligand classes into one. All results were confirmed by three independent data sets. Focusing on very reliably predicted residues could complement experimental evidence: For the 25% most strongly predicted binding residues, at least 73% were correctly predicted even when ignoring the problem of missing experimental annotations. The new method bindEmbed21 is fast, simple, and broadly applicable - neither using structure nor MSAs. Thereby, it found binding residues in over 42% of all human proteins not otherwise implied in binding and predicted about 6% of all residues as binding to metal ions, nucleic acids, or small molecules.


title: Defining the extent of gene function using ROC curvature

abstract: Machine learning in genomics plays a key role in leveraging high-throughput data, but assessing the generalizability of performance has been a persistent challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves. We identify Functional Equivalence Classes (FECs), uniform subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves. FECs are widespread across modalities and methods, and can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10 to 50 genes), and tissue-specific secondary markers (100 to 500{square}genes). In addition, FECs are compatible with a wide range of functional encodings, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in analysis.


title: Properties of Photosystem II lacking the PsbJ subunit

abstract: Photosystem II (PSII), the oxygen-evolving enzyme, consists of 17 trans-membrane and 3 extrinsic membrane proteins. Other subunits bind to PSII during assembly, like Psb27, Psb28, Tsl0063. The presence of Psb27 has been proposed (Zabret et al. 2021; Huang et al. 2021; Xiao et al. 2021) to prevent the binding of PsbJ, a single transmembrane -helix close to the quinone QB binding site. Consequently, a PSII rid of Psb27, Psb28 and Tsl0034 prior to the binding of PsbJ would logically correspond to an assembly intermediate. The present work describes experiments aiming at further characterizing such a {Delta}PsbJ-PSII, purified from the thermophilic Thermosynechococcus elongatus, by means of MALDI-TOF spectroscopy, Thermoluminescence, EPR spectroscopy and UV-visible time-resolved spectroscopy. In the purified {Delta}PsbJ-PSII, an active Mn4CaO5 cluster is present in 60-70 % of the centers. In these centers, although the forward electron transfer seems not affected, the Em of the QB/QB- couple increases by [≥] 120 mV thus disfavoring the electron coming back on QA. The increase of the energy gap between QA/QA- and QB/QB- could contribute in a protection against the charge recombination between the donor side and QB-, identified at the origin of photoinhibition under low light (Keren et al. 1997), and possibly during the slow photoactivation process.

category: biophysics


title: Comprehensive cancer-oriented biobanking resource of human samples for studies of post-zygotic genetic variation involved in cancer predisposition

abstract: The progress in translational cancer research relies on access to well-characterized samples from a representative number of patients and controls. The rationale behind our biobanking are explorations of post-zygotic pathogenic gene variants, especially in non-tumoral tissue, which might predispose to cancers. The targeted diagnoses are carcinomas of the breast (via mastectomy or breast conserving surgery), colon and rectum, prostate, and urinary bladder (via cystectomy or transurethral resection), exocrine pancreatic carcinoma as well as metastases of colorectal cancer to the liver. The choice was based on the high incidence of these cancers and/or frequent fatal outcome. We also collect age-matched normal controls. Our still ongoing collection originates from five clinical centers and after nearly 2-year cooperation reached 1711 patients and controls, yielding a total of 23226 independent samples, with an average of 74 donors and 1010 samples collected per month. The predominant diagnosis is breast carcinoma, with 933 donors, followed by colorectal carcinoma (383 donors), prostate carcinoma (221 donors), bladder carcinoma (81 donors), exocrine pancreatic carcinoma (15 donors) and metachronous colorectal cancer metastases to liver (14 donors). Forty percent of the total sample count originates from macroscopically healthy cancer-neighboring tissue, while contribution from tumors is 12%, which adds to the uniqueness of our collection for cancer predisposition studies. Moreover, we developed two program packages, enabling registration of patients, clinical data and samples at the participating hospitals as well as the central system of sample/data management at coordinating center. The approach used by us may serve as a model for dispersed biobanking from multiple satellite hospitals. Our biobanking resource ought to stimulate research into genetic mechanisms underlying the development of common cancers. It will allow all available "-omics" approaches on DNA-, RNA-, protein- and tissue levels to be applied. The collected samples can be made available to other research groups.

category: cancer biology


title: Parenteral glucose supply and pharmacological glycolysis inhibition determine the clinical fate of infected preterm newborns

abstract: Preterm infants are susceptible to bloodstream infection that can lead to sepsis. High parenteral glucose supplement is commonly used to support their growth and energy expenditure, but may exceed endogenous regulation during infection, causing dysregulated immune response and clinical deterioration. Using a preterm piglet model of neonatal sepsis induced by Staphylococcus epidermidis infection, we demonstrate the delicate interplay between immunity and energy metabolism to regulate the host infection response. Circulating glucose levels, glycolysis and inflammatory response to infection are closely connected across the states of tolerance, resistance and immunoparalysis. Further, high parenteral glucose provision during infection induces hyperglycemia, elevated glycolysis and inflammation, leading to lactate acidosis and sepsis, whereas glucose restricted individuals are clinically unaffected with increased gluconeogenesis to maintain moderate hypoglycemia. Finally, pharmacological glycolysis inhibition during normoglycemia enhances bacterial clearance and dampens inflammation but fails to prevent sepsis. Our results uncover how blood glucose controls immune cell metabolism and function, in turn determining the clinical fate of infected preterm neonates. This also questions the current practice of parenteral glucose supply for infected preterm infants.

category: pathology


title: Silencing of hippocampal synaptic transmission impairs spatial reward search on a head-fixed tactile treadmill task

abstract: Head-fixed linear treadmill tasks have been used to study hippocampal physiology in mice. Although some hippocampal neurons establish place fields along linear treadmills, it is not clear if the hippocampus is required for spatial memory on this task. Using a Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) approach, we found that silencing hippocampal output on rewarded treadmill tasks impaired search for rewards signaled by spatial cues but did not impair search for rewards signaled by local cues, recapitulating findings from other behavior tasks. These findings serve to contextualize data on hippocampal physiology from mice performing this task.

category: neuroscience


title: Collagen VI regulates motor circuit plasticity and motor performance by cannabinoid modulation

abstract:
Collagen VI is a key component of muscle basement membranes, and genetic variants can cause monogenic muscular dystrophies. Conversely, human genetic studies recently implicated collagen VI in central nervous system function, with variants causing the movement disorder dystonia. To elucidate the neurophysiological role of collagen VI, we generated mice with a truncation of the dystonia-related collagen 3 (VI) (COL6A3) C-terminal domain (CTD). These Col6a3CTT mice showed a recessive dystonia-like phenotype. We found that COL6A3 interacts with the cannabinoid receptor 1 (CB1R) complex in a CTD-dependent manner. Col6a3CTT mice have impaired homeostasis of excitatory input to the basal pontine nuclei (BPN), a motor control hub with dense COL6A3 expression, consistent with deficient endocannabinoid signaling. Aberrant synaptic input in the BPN was normalized by a CB1R agonist, and motor performance in Col6a3CTT mice was improved by CB1R agonist treatment. Our findings identify a readily therapeutically addressable synaptic mechanism for motor control.

SIGNIFICANCE STATEMENTDystonia is a movement disorder characterized by involuntary movements. We previously identified genetic variants affecting a specific domain of the COL6A3 protein as a cause of dystonia. Here, we we created mice lacking the affected domain and observed an analogous movement disorder. Using a protein interaction screen, we found that the affected COL6A3 domain mediates an interaction with the cannabinoid receptor CB1R. Concordantly, our COL6A3-deficient mice showed a deficit in synaptic plasticity linked to a deficit in cannabinoid signaling. Pharmacological cannabinoid augmentation rescued the motor impairment of the mice. Thus, cannabinoid augmentation could be a promising avenue for treating dystonia, and we have identified a possible molecular mechanism mediating this.


title: Rapid dynamic naturalistic monitoring of bradykinesia in Parkinson's disease using a wrist-worn accelerometer

abstract:
IntroductionMotor fluctuations in Parkinsons disease are characterized by unpredictability in the timing and duration of dopaminergic therapeutic benefit on symptoms including bradykinesia and rigidity. These fluctuations significantly impair the quality of life of many Parkinsons patients. However, current clinical evaluation tools are not designed for the continuous, naturalistic (real-world) symptom monitoring needed to optimize clinical therapy to treat fluctuations. Although commercially available wearable motor monitoring, used over multiple days, can augment neurological decision making, the feasibility of rapid and dynamic detection of motor fluctuations is unclear. So far, applied wearable monitoring algorithms are trained on group data. Here, we investigate the influence of individual model training on short timescale classification of naturalistic bradykinesia fluctuations in Parkinsons patients using a single wrist-accelerometer.

MethodsAs part of the Parkinson@Home study protocol, 20 Parkinson patients were recorded with bilateral wrist-accelerometers for a one hour OFF medication session and a one hour ON medication session during unconstrained activities in their own homes. Kinematic metrics were extracted from the accelerometer data from the bodyside with the largest unilateral bradykinesia fluctuations across medication states. The kinematic accelerometer features were compared over the whole one-hour recordings, and medication-state classification analyses were performed on one-minute segments of data. The influence of individual versus group model training, data window length, and total amount of training patients included in group model training on classification was analyzed.

ResultsStatistically significant areas under the curves (AUCs) for medication induced bradykinesia fluctuation classification were seen in 85% of the Parkinson patients at the single minute timescale using the group models. Individually trained models performed at the same level as the group trained models (mean AUC both 0.70, +/- respectively 0.18 and 0.10) despite the small individual training dataset. AUCs of the group models improved as the length of the feature windows was increased to 300 seconds, and with additional training patient datasets.

ConclusionMedication induced fluctuations in bradykinesia can be classified using wrist worn accelerometery at the time scale of a single minute. Rapid, naturalistic Parkinson motor monitoring has important clinical potential to evaluate dynamic symptomatic and therapeutic fluctuations and help tailor treatments on a fast timescale.


title: Mathematical modelling of autoimmune myocarditis and the effects of immune checkpoint inhibitors

abstract: Autoimmune myocarditis is a rare, but frequently fatal, side effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite extensive experimental work on the causes, development and progression of this disease, much still remains unknown about the importance of the different immunological pathways involved. We present a mathematical model of autoimmune myocarditis and the effects of ICIs on its development and progression to either resolution or chronic inflammation. From this, we gain a better understanding of the role of immune cells, cytokines and other components of the immune system in driving the cardiotoxicity of ICIs. We parameterise the model using existing data from the literature, and show that qualitative model behaviour is consistent with disease characteristics seen in patients in an ICI-free context. The bifurcation structures of the model show how the presence of ICIs increases the risk of developing autoimmune myocarditis. This predictive modelling approach is a first step towards determining treatment regimens that balance the benefits of treating cancer with the risk of developing autoimmune myocarditis.

category: immunology


title: Bioactive exometabolites drive maintenance competition in simple bacterial communities

abstract: During prolonged resource limitation, bacterial cells can persist in metabolically active states of non-growth. These maintenance periods, such as those experienced in stationary phase, can include upregulation of secondary metabolism and release of exometabolites into the local environment. As resource limitation is common of many environmental microbial habitats, we hypothesized that neighboring bacterial populations employ exometabolites to compete or cooperate during maintenance, and that these exometabolite-facilitated interactions can drive community outcomes. Here, we evaluated the consequences of exometabolite interactions over stationary phase among three environmental strains: Burkholderia thailandensis E264, Chromobacterium subtsugae, and Pseudomonas syringae pv.tomato DC3000. We assembled them into synthetic communities that only permitted chemical interactions. We compared the responses (transcripts) and outputs (exometabolites) of each member with and without neighbors. We found that transcriptional dynamics were changed with different neighbors, and that some of these changes were coordinated between members. The dominant competitor B. thailandensis consistently upregulated biosynthetic gene clusters to produce bioactive exometabolites for both exploitative and interference competition. These results demonstrate that competition strategies during maintenance can contribute to community-level outcomes. It also suggests that the traditional concept of defining competitiveness by growth outcomes may be narrow, and that maintenance competition could be an alternative measure.

category: microbiology


title: Coherent Gene Assemblies: Example, Yeast Cell Division Cycle, CDC

abstract:
A fresh approach to the dynamics of gene assemblies is presented. Central to the exposition are the concepts of: high value genes; correlated activity; and the orderly unfolding of gene dynamics; and especially dynamic mode decomposition, DMD, a remarkable new tool for dissecting dynamics. This program is carried out, in detail, for the Orlando et al yeast database (Orlando et al. 2008).

It is shown that the yeast cell division cycle, CDC, requires no more than a six dimensional space, formed by three complex temporal modal pairs, each associated with characteristic aspects of the cell cycle: (1) A mother cell cohort that follows a fast clock; (2) A daughter cell cohort that follows a slower clock; (3) inherent gene expression, unrelated to the CDC.

A derived set of sixty high-value genes serves as a model for the correlated unfolding of gene activity. Confirmation of our results comes from an independent database, and other considerations. The present analysis, leads naturally, to a Fourier description, for the sparsely sampled data. From this, resolved peak times of gene expression are obtained. This in turn leads to prediction of precise times of expression in the unfolding of the CDC genes. The activation of each gene appears as uncoupled dynamics from the mother and daughter cohorts, of different durations. These deliberations lead to detailed estimates of the fraction of mother and daughter cells, specific estimates of their maturation periods, and specific estimates of the number of genes in these cells.

An algorithmic framework for yeast modeling is proposed, and based on the new analyses, a range of theoretical ideas and new experiments are suggested.

A Supplement contains additional material and other perspectives.

category: molecular biology


title: Sex Chromosome Heteromorphism and the Fast-X Effect in Poeciliids

abstract: An accelerated rate of sequence evolution on the X chromosome compared to autosomes, known as Fast-X evolution, has been observed in a range of heteromorphic sex chromosomes. However, it remains unclear how early in the process of sex chromosome differentiation the Fast-X effect becomes detectible. Recently, we uncovered an extreme variation in sex chromosome heteromorphism across Poeciliid fish species. The common guppy, Poecilia reticulata, Endlers guppy, P. wingei, and the swamp guppy, P. picta, appear to share the same XY system and exhibit a remarkable range of heteromorphism. The sex chromosome system is absent in recent outgroups, including P. latipinna and Gambusia holbrooki. We combined analyses of sequence divergence and polymorphism data across Poeciliids to investigate X chromosome evolution as a function of hemizygosity and reveal the causes for Fast-X effects. Consistent with the extent of Y degeneration in each species, we detect higher rates of divergence on the X relative to autosomes and a strong Fast-X effect in P. picta, while no change in the rate of evolution of X-linked relative to autosomal genes in P. reticulata. In P. wingei, the species with intermediate sex chromosome differentiation, we see an increase in the rate of nonsynonymous substitutions on the older stratum of divergence only. We also use our comparative approach to test different models for the origin of the sex chromosomes in this clade. Taken together, our study reveals an important role of hemizygosity in Fast-X and suggests a single, recent origin of the sex chromosome system in this clade.


title: Prediction of evolutionary constraint by genomic annotations improves prioritization of causal variants in maize

abstract: Crop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at single-site resolution. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we used genomic annotations to accurately predict nucleotide conservation across Angiosperms, as a proxy for fitness effect of mutations. Using only sequence analysis, we annotated non-synonymous mutations in 25,824 maize gene models, with information from bioinformatics (SIFT scores, GC content, transposon insertion, k-mer frequency) and deep learning (predicted effects of polymorphisms on protein representations by UniRep). Our predictions were validated by experimental information: within-species conservation, chromatin accessibility, gene expression and gene ontology enrichment. Importantly, they also improved genomic prediction for fitness-related traits (grain yield) in elite maize panels (+5% and +38% prediction accuracy within and across panels, respectively), by stringent prioritization of [≤] 1% of single-site variants (e.g., 104 sites and approximately 15deleterious alleles per haploid genome). Our results suggest that predicting nucleotide conservation across Angiosperms may effectively prioritize sites most likely to impact fitness-related traits in crops, without being limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Our approach - Prediction of mutation Impact by Calibrated Nucleotide Conservation (PICNC) - could be useful to select polymorphisms for accurate genomic prediction, and candidate mutations for efficient base editing.


title: Generation of transducible version of a recombinant human HAND2 transcription factor from Escherichia coli

abstract: Transcription factor HAND2 has a significant role in vascularization, angiogenesis, and cardiac neural crest development. Also, it is one of the key cardiac factors crucial for the enhanced derivation of functional and mature myocytes from non-myocyte cells. Here, we report the generation of the recombinant human HAND2 fusion protein from the heterologous system. First, we cloned the full-length human HAND2 gene (only protein-coding sequence) after codon optimization along with the fusion tags (for cell penetration, nuclear translocation, and affinity purification) into the expression vector. We then transformed and expressed it in Escherichia coli (E. coli) strain, BL21(DE3). Next, the effect (in terms of expression) of tagging of fusion tags with this recombinant protein at two different terminals was also investigated. Notably, using affinity chromatography, we established the one-step homogeneous purification of human recombinant HAND2 protein; and through circular dichroism spectroscopy, we established that this purified protein had retained its secondary structure. Furthermore, we show that this purified human protein could transduce the human cells and translocate to its nucleus. Prospectively, the purified recombinant HAND2 protein can potentially be a safe and effective molecular tool in the direct cardiac reprogramming process and other biological applications.

category: bioengineering


title: Integrative multi-omics identifies high risk Multiple Myeloma segment associated with significant DNA loss and dysregulated DNA repair and cell cycle pathways

abstract:
Despite significant therapeutic advances in improving lives of Multiple Myeloma (MM) patients, it remains mostly incurable, with patients ultimately becoming refractory to therapies. MM is a genetically heterogeneous disease and therapeutic resistance is driven by a complex interplay of disease pathobiology and mechanisms of drug resistance. We applied a multi-omics strategy using tumor-derived gene expression, single nucleotide variant, copy number variant, and structural variant profiles to investigate molecular subgroups in 514 newly diagnosed MM (NDMM) samples and identified 12 molecularly defined MM subgroups (MDMS1-12) with distinct genomic and transcriptomic features.

Our integrative approach let us identify ndMM subgroups with transversal profiles to previously described ones, based on single data types, which shows the impact of this approach for disease stratification. One key novel subgroup is our MDMS8, associated with poor clinical outcome [median overall survival, 38 months (global log-rank pval<1x10-6)], which uniquely presents a broad genomic loss (>9% of entire genome, t.test pval<1e-5) driving dysregulation of various transcriptional programs affecting DNA repair and cell cycle/mitotic processes. This subgroup was validated on multiple independent datasets, and a master regulator analyses identified transcription factors controlling MDMS8 transcriptomic profile, including CKS1B and PRKDC among others, which are regulators of the DNA repair and cell cycle pathways.

Statement of SignificanceUsing multi-omics unsupervised clustering we discovered a new high-risk multiple myeloma patient segment. We linked its diverse genetic markers (previously known, and new including genomic loss) to transcriptional dysregulation (cell cycle, DNA repair and DNA damage) and identified master regulators that control these key biological pathways.


title: Enhancer-priming in ageing human bone marrow mesenchymal stromal cells contributes to immune traits

abstract: Bone marrow mesenchymal stromal cells (BMSCs) can differentiate into adipocytes and osteoblasts, and are important regulators of the haematopoietic system. Ageing associates with an increased ratio of bone marrow adipocytes to osteoblasts and immune dysregulation. Here, we carried out an integrative multiomics analysis of ATAC-Seq, RNA-Seq and proteomics data from primary human BMSCs in a healthy cohort age between 20 - 60. We identified age-sensitive elements uniquely affecting each molecular level where transcription is mostly spared, and characterised the underlying biological pathways, revealing the interplay of age-related gene expression mechanism changes spanning multiple gene regulatory layers. Through data integration with enhancer-mediated gene regulatory network analysis, we discovered that enhancers and transcription factors influence cell differentiation potential in the ageing BMSCs. By combining our results with genome-wide association study data, we found that age-specific changes could contribute to common traits related to BMSC-derived tissues such as bone and adipose tissue, and to immune-related traits on a systemic level such as asthma. We demonstrate here that a multiomics approach is crucial for unravelling complex information, providing new insights on how ageing contributes to bone marrow- and immune-related disorders.

category: systems biology


title: The evolution of open habitats in North America revealed by deep learning models

abstract: Open vegetation today constitutes one of the most extensive biomes on earth, including temperate grasslands and tropical savannas. Yet these biomes originated relatively recently in earth history, likely replacing forested habitats as recently as the second half of the Cenozoic, although the timing of their origination and the dynamics of their expansion remain uncertain. Here, we present a new hypothesis of paleovegetation change in North America, showing that open habitats originated between 25 and 20 Ma in the center of the continent, and expanded rapidly starting 8 Ma to eventually become the most prominent vegetation type today. To obtain space-time predictions of paleovegetation, we developed a new Bayesian deep learning model that utilizes available information from fossil evidence, geologic models, and paleoclimate proxies. We compiled a large dataset of paleovegetation reconstructions from the peer-reviewed literature, which we used in combination with current vegetation data to train the model. The model learns to predict vegetation based on the learned associations between the vegetation at a given site and multiple biotic and abiotic predictors: fossil mammal occurrences, plant macrofossils, estimates of temperature and precipitation, latitude, and the effects of spatial and temporal autocorrelation. Our results provide a new, spatially detailed reconstruction of habitat evolution in North America and our deep learning model paves the way for a new quantitative approach to estimating paleovegetation changes.


title: Can deep convolutional neural networks support relational reasoning in the same-different task?

abstract: Same-different visual reasoning is a basic skill central to abstract combinatorial thought. This fact has lead neural networks researchers to test same-different classification on deep convolutional neural networks (DCNNs), which has resulted in a controversy regarding whether this skill is within the capacity of these models. However, most tests of same-different classification rely on testing on images that come from the same pixel-level distribution as the testing images, yielding the results inconclusive. In this study we tested relational same-different reasoning DCNNs. In a series of simulations we show that models based on the ResNet-50 architecture are capable of visual same-different classification, but only when the test images are similar to the training images at the pixel-level. In contrast, even when there are only subtle differences between the testing and training images, the performance of DCNNs drops substantially. This is true even when DCNNs training regime is augmented with images from new versions of the same-different task or through multi-task learning on the test images. Furthermore, we show that the Relation Network, a deep learning architecture specifically designed to tackle visual relational reasoning problems, suffers the same kind of limitations than ResNet-50 classifiers.

category: animal behavior and cognition


title: Emergent intra-pair sex differences and behavioral coordination in pair bonded prairie voles

abstract: In pair bonding animals, coordinated behavior between partners is required for the pair to accomplish shared goals such as raising young. Despite this, experimental designs rarely assess the behavior of both partners within a bonded pair. Thus, we lack an understanding of the interdependent behavioral dynamics between partners that likely facilitate relationship success. To identify intra-pair behavioral correlates of pair bonding, we used socially monogamous prairie voles, a species in which females and males exhibit both overlapping and distinct pair bond behaviors. We tested both partners using social choice and non-choice tests at short- and long-term pairing timepoints. Females developed a preference for their partner more rapidly than males, with preference driven by different behaviors in each sex. Further, as bonds matured, intra-pair behavioral sex differences and coordinated behavior emerged - females consistently huddled more with their partner than males did, and partner huddle time became correlated between partners. When animals were allowed to freely interact with a partner or a novel in sequential free interaction tests, pairs spent more time interacting together than either animal did with a novel. Pair interaction was correlated with female, but not male, behavior. Via a social operant paradigm, we found that pair-bonded females, but not males, are more motivated to access and huddle with their partner than a novel vole. Together, our data indicate that as pair bonds mature, sex differences and coordinated behavior emerge, and that these intra-pair behavioral changes are likely organized and driven by the female animal.


title: Improve consensus partitioning via a hierarchical procedure

abstract: Consensus partitioning is an unsupervised method widely used in high throughput data analysis for revealing subgroups and assigns stability for the classification. However, standard consensus partitioning procedures are weak to identify large numbers of stable subgroups. There are two main issues. 1. Subgroups with small differences are difficult to separate if they are simultaneously detected with subgroups with large differences. And 2. stability of classification generally decreases as the number of subgroups increases. In this work, we proposed a new strategy to solve these two issues by applying consensus partitionings in a hierarchical procedure. We demonstrated hierarchical consensus partitioning can be efficient to reveal more subgroups. We also tested the performance of hierarchical consensus partitioning on revealing a great number of subgroups with a DNA methylation dataset. The hierarchical consensus partitioning is implemented in the R package cola with comprehensive functionality for analysis and visualizations. It can also automate the analysis only with a minimum of two lines of code, which generates a detailed HTML report containing the complete analysis.


title: ProteinPrompt: a webserver for predictingprotein-protein interactions

abstract:
MotivationProtein-protein interactions play an essential role in a great variety of cellular processes and are therefore of significant interest for the design of new therapeutic compounds as well as the identification of side-effects due to unexpected binding. Here, we present ProteinPrompt, a webserver that uses machine-learning algorithms to calculate specific, currently unknown protein-protein interactions. Our tool is designed to quickly and reliably predict contacts based on an input sequence in order to scan large sequence libraries for potential binding partners, with the goal to accelerate and assure the quality of the laborious process of drug target identification.

MethodsWe collected and thoroughly filtered a comprehensive database of known contacts from several sources, which is available as download. ProteinPrompt provides two complementary search methods of similar accuracy for comparison and consensus building. The default method is a random forest algorithm that uses the auto-correlations of seven amino acid scales. Alternatively, a graph neural network implementation can be selected. Additionally, a consensus prediction is available. For each query sequence, potential binding partners are identified from a protein sequence database. The proteom of several organisms are available and can be searched for contacts.

ResultsTo evaluate the predictive power of the algorithms, we prepared a test dataset that was rigorously filtered for redundancy. No sequence pairs similar to the ones used for training were included in this dataset. With this challenging dataset, the random forest method achieved an accuracy rate of 0.88 and an area under curve of 0.95. The graph neural network achieved an accuracy rate of 0.86 using the same dataset. Since the underlying learning approaches are unrelated, comparing the results of random forest and graph neural networks reduces the likelihood of errors. The consensus reached an accuracy of 0.89. ProteinPrompt is available online at: http://proteinformatics.org/ProteinPrompt

The server makes it possible to scan the human proteome for potential binding partners of an input sequence within minutes. For local offline usage, we furthermore created a ProteinPrompt Docker image which allows for batch submission: https://gitlab.hzdr.de/Proteinprompt/ProteinPrompt. In conclusion, we offer a fast, accurate, easy-to-use online service for predicting binding partners from an input sequence.


title: ProteinPrompt: a webserver for predicting protein-protein interactions


title: Network Modeling Predicts Personalized Gene Expression and Drug Responses in Valve Myofibroblasts Cultured with Patient Sera

abstract: Aortic valve stenosis (AVS) patients experience pathogenic valve leaflet stiffening due to excessive extracellular matrix (ECM) remodeling. Numerous microenvironmental cues influence pathogenic expression of ECM remodeling genes in tissue-resident valvular myofibroblasts, and the regulation of complex myofibroblast signaling networks depends on patient-specific extracellular factors. Here, we combined a manually curated myofibroblast signaling network with a data-driven transcription factor network to predict patient-specific myofibroblast gene expression signatures and drug responses. Using transcriptomic data from myofibroblasts cultured with AVS patient sera, we produced a large-scale, logic-gated differential equation model in which 11 biochemical and biomechanical signals are transduced via a network of 334 signaling and transcription reactions to accurately predict the expression of 27 fibrosis-related genes. Correlations were found between personalized model-predicted gene expression and AVS patient echocardiography data, suggesting links between fibrosis-related signaling and patient-specific AVS severity. Further, global network perturbation analyses revealed signaling molecules with the most influence over network-wide activity including endothelin 1 (ET1), interleukin 6 (IL6), and transforming growth factor {beta} (TGF{beta}) along with downstream mediators c-Jun N-terminal kinase (JNK), signal transducer and activator of transcription (STAT), and reactive oxygen species (ROS). Lastly, we performed virtual drug screening to identify patient-specific drug responses, which were experimentally validated via fibrotic gene expression measurements in VICs cultured with AVS patient sera and treated with or without bosentan - a clinically approved ET1 receptor inhibitor. In sum, our work advances the ability of computational approaches to provide a mechanistic basis for clinical decisions including patient stratification and personalized drug screening.


title: Inverse Problem Reveals Conditions for Characteristic Retinal Degeneration Patterns in Retinitis Pigmentosa under the Trophic Factor Hypothesis

abstract: Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy with a prevalence of about 1 in 4000, affecting approximately 1.5 million people worldwide. Patients with RP experience progressive visual field loss as the retina degenerates, destroying light-sensitive photoreceptor cells (rods and cones), with rods affected earlier and more severely than cones. Spatio-temporal patterns of retinal degeneration in human RP have been well characterised; however, the mechanism(s) giving rise to these patterns have not been conclusively determined. One such mechanism, which has received a wealth of experimental support, is described by the trophic factor hypothesis. This hypothesis suggests that rods produce a trophic factor necessary for cone survival; the loss of rods depletes this factor, leading to cone degeneration. In this paper we formulate a partial differential equation mathematical model of RP in one spatial dimension, spanning the region between the retinal centre (fovea) and the retinal edge (ora serrata). Using this model we derive and solve an inverse problem, revealing for the first time experimentally testable conditions under which the trophic factor mechanism will qualitatively recapitulate the spatio-temporal patterns of retinal regeneration observed in human RP.


title: CluSem: Accurate Clustering-based Ensemble Methodto Predict Motor Imagery Tasks from Multi-channelEEG Data

abstract:
BackgroundThe classification of motor imagery electroencephalogram (MI-EEG) is a pivotal task in the biosignal classification process in the brain-computer interface (BCI) applications. Currently, this bio-engineering-based technology is being employed by researchers in various fields to develop cuttingedge applications. The classification of real-time MI-EEG signals is the most challenging task in these applications. The prediction performance of the existing classification methods is still limited due to the high dimensionality and dynamic behaviors of the real-time EEG data.

Proposed MethodTo enhance the classification performance of real-time BCI applications, this paper presents a new clustering-based ensemble technique called CluSem to mitigate this problem. We also develop a new brain game called CluGame using this method to evaluate the classification performance of real-time motor imagery movements. In this game, real-time EEG signal classification and prediction tabulation through animated balls are controlled via threads. By playing this game, users can control the movements of the balls via the brain signals of motor imagery movements without using any traditional input devices.

ResultsOur results demonstrate that CluSem is able to improve the classification accuracy between 5% and 15% compared to the existing methods on our collected as well as the publicly available EEG datasets. The source codes used to implement CluSem and CluGame are publicly available at https://github.com/MdOchiuddinMiah/MI-BCI_ML.


title: Movement-Dependent Electrical Stimulation for Volitional Strengthening of Cortical Connections in Behaving Monkeys

abstract:
Correlated activity of neurons can lead to long-term strengthening or weakening of the connections between them. In addition, the behavioral context, imparted by execution of physical movements or the presence of a reward, can modulate the plasticity induced by Hebbian mechanisms. In the present study, we have combined behavior and induced neuronal correlations to strengthen connections in the motor cortex of adult behaving monkeys. Correlated activity was induced using an electrical-conditioning protocol in which stimuli gated by voluntary movements were used to produce co-activation of neurons at motor-cortical sites involved in those movements. Delivery of movement-dependent stimulation resulted in small increases in the strength of associated cortical connections immediately after conditioning. Remarkably, when paired with further repetition of the movements that gated the conditioning stimuli, there were substantially larger gains in the strength of cortical connections, that occurred in a use-dependent manner, without delivery of additional conditioning stimulation. In the absence of such movements, little change was observed in the strength of motor-cortical connections. Performance of the motor behavior in the absence of conditioning also did not produce any changes in connectivity. Our results show that combining movement-gated stimulation with further natural use of the "conditioned" pathways after stimulation ends can produce use-dependent strengthening of connections in adult primates, highlighting an important role for behavior in cortical plasticity. Our data also provide strong support for combining movement-gated stimulation with use-dependent physical rehabilitation for strengthening connections weakened by a stroke or spinal-cord injury.

Significance StatementWe describe an electrical-conditioning protocol in adult behaving monkeys in which stimuli gated by voluntary movements were used to strengthen connections between motor-cortical neurons involved in those movements. Movement-gated stimulation created a plastic landscape in which repetition of the movements that gated conditioning stimuli produced strengthening of cortical connections, in a use-dependent manner, long after stimulation had ended, a finding that is both novel and unique. In the absence of such behavior, little change was observed in the strength of connections. Similarly, movements alone did not produce any changes in connectivity. Our data highlight a critical role for behavior in plasticity and provide strong support for combining movement-gated stimulation with use-dependent rehabilitation for strengthening connections weakened by injury or disease.


title: Pilot identification of the Live-1/Prox-1 expressing lymphatic vessels and lymphatic elements in the unaffected and affected human brain

abstract:
We report here a pilot identification of the presence of the lumenized Lyve-1/Prox-1-expressing vessels with distinct walls composed of a single endothelial layer in the unaffected brain and with intraventricular hemorrhages. These lymphatic vessels (LVs) have valves and an undulating shape in the distal region that is the classical characteristic of lymphatic precollectors. Furthermore, we identified Lyve-1/Prox-1-expressing lymphatic elements in the enlarged perivascular spaces. These pioneering results might be a revolutionary step in our understanding of anatomy and physiology of the cerebral lymphatics and stimulate a reassessment of basic assumptions in the aetiology of brain diseases associated with lymphatic dysfunction. The discovery of the cerebral LVs is a crucial step in the development of breakthrough technologies of modulations of lymphatic removing of toxins and blood from the brain.

One Sentence SummaryLyve1/Prox1-expressing lymphatic vessels and elements in the unaffected and affected human brain.


title: Predicting mind wandering episodes quarter hours in advances from EEG

abstract: Mind wandering occurs when spontaneous thought generation is increased while cognitive control is decreased, presumably in response to antagonistic effects of default mode-(DMN) and goal-directed network (GDN) activity. Previous studies assumed that DMN or GDN activity manifests in behavior with minimal delays and has rigid effects, i.e., DMN always facilitates generation of spontaneous thought and inhibits cognitive control. With those static response functions, the antagonism of DMN and GDN could explain the alternation of task focused and mind wandering states. But it rules out others, such as multi-tasking, where spontaneous thought and cognitive control are both increased, or rumination, where both are decreased. However, shifts from task focused to mind wandering have been shown to occur via a multi-tasking state. We therefore propose dynamic response functions, allowing delay or reversal of DMN and GDN effects. Dynamic response functions enabled us to stochastically predict mind wandering up to at least 30 min in advance from EEG measures of DMN and GDN activity in a tone counting task. Experimental results show both considerable delays and switches between task-positive and negative effects. Mind wandering was initiated by a barrage of DMN activity more than 20 minutes prior a report of mind wandering, directing the mental focus inward. Critically, facilitation of spontaneous thoughts occurred several minutes prior to the report. These thoughts sustained up to 10 min, after which a rebound to task-focused behavior was effectuated, notably without intervention from the GDN. Repeated GDN interventions, however, secured a basic level of task performance.


title: Neurons in the dorsomedial hypothalamus promote, prolong, and deepen torpor

abstract:
Torpor is a naturally occurring, hypometabolic, hypothermic state engaged by a wide range of animals in response to imbalance between the supply and demand for nutrients. Recent work has identified some of the key neuronal populations involved in daily torpor induction in mice, in particular projections from the preoptic area of the hypothalamus (POA) to the dorsomedial hypothalamus (DMH). The DMH plays a role in thermoregulation, control of energy expenditure, and circadian rhythms, making it well positioned to contribute to the expression of torpor. We used activity dependent genetic TRAPing techniques to target DMH neurons that were active during natural torpor bouts in female mice. Chemogenetic reactivation of torpor-TRAPed DMH neurons in calorie-restricted mice promoted torpor, resulting in longer and deeper torpor bouts. Chemogenetic inhibition of torpor-TRAPed DMH neurons did not block torpor entry, suggesting a modulatory role for the DMH in the control of torpor. This work adds to the evidence that the POA and the DMH form part of a circuit within the mouse hypothalamus that controls entry into daily torpor.

SignificanceDaily heterotherms such as mice employ torpor to cope with environments in which the supply of metabolic fuel is not sufficient for the maintenance of normothermia. Daily torpor involves reductions in body temperature, as well as active suppression of heart rate and metabolism. How the central nervous system controls this profound deviation from normal homeostasis is not known, but a projection from the preoptic area to the dorsomedial hypothalamus has recently been implicated. We demonstrate that the dorsomedial hypothalamus contains neurons that are active during torpor. Activity in these neurons promotes torpor entry and maintenance, but their activation alone does not appear to be sufficient for torpor entry.


title: Interrelations between delta waves, spindles and slow oscillations in human NREM sleep and their functional role in memory

abstract:
Certain neurophysiological characteristics of sleep, in particular slow oscillations (SO), sleep spindles, and their temporal coupling, have been well characterized and associated with human memory formation. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SO, have only recently been found to play a critical role in memory processing of rodents, through a competitive interplay between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta waves, their interactions with spindles and SOs as well as their functional role for memory are still lacking.

Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories.

Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found that increased delta activity was accompanied by stronger SO-spindle coupling. Moreover, we identified the ratio between SO- and delta-nested spindles as the sleep parameter that predicted ability to form novel memories best.

Our study suggests that SOs, delta waves and sleep spindles should be jointly considered when aiming to link sleep physiology and memory formation in aging.

Significance statementInterrelations between delta waves, slow oscillations and sleep spindles have recently been causally linked to the balance between consolidation and forgetting in rats using optogenetics. In humans, SO-spindle coupling has been intensively investigated, but delta waves and their interaction with spindles were only studied jointly as SWA. Here we delineate the coupling of delta waves to spindles, investigate interactions of delta- and SO-related activity and investigate their role for the ability to form novel memories in healthy older individuals. Our results show differences as well as dependencies between SO- and delta-related activities including spindle coupling. Further, our results indicate that the ratio of SO- to delta-nested spindles might be the most informative sleep parameter for memory formation of older adults.


title: Medullary vein architecture modulates the white matter BOLD cerebrovascular reactivity signal response to CO2: observations from high-resolution T2* weighted imaging at 7T

abstract: Brain stress testing using blood oxygenation level-dependent (BOLD) MRI to evaluate changes in cerebrovascular reactivity (CVR) is of growing interest for evaluating white matter integrity. However, even under healthy conditions, the white matter BOLD-CVR response differs notably from that observed in the gray matter. In addition to actual arterial vascular control, the venous draining topology may influence the WM-CVR response leading to signal delays and dispersions. These types of alterations in hemodynamic parameters are sometimes linked with pathology, but may also arise from differences in normal venous architecture. In this work, high-resolution T2*weighted anatomical images combined with BOLD imaging during a hypercapnic breathing protocol were acquired using a 7 tesla MRI system. Hemodynamic parameters including base CVR, hemodynamic lag, lag-corrected CVR, response onset and signal dispersion, and finally {Delta}CVR (corrected CVR minus base CVR) were calculated in 8 subjects. Parameter maps were spatially normalized and correlated against an MNI-registered white matter medullary vein atlas. Moderate correlations (Pearsons rho) were observed between medullary vessel frequency (MVF) and {Delta}CVR (0.52; 0.58 for total WM), MVF and hemodynamic lag (0.42; 0.54 for total WM), MVF and signal dispersion (0.44; 0.53 for total WM), and finally MVF and signal onset (0.43; 0.52 for total WM). Results indicate that, when assessed in the context of the WM venous architecture, changes in the response shape may only be partially reflective of the actual vascular reactivity response occurring further upstream by control vessels. This finding may have implications when attributing diseases mechanisms and/or progression to presumed impaired WM BOLD-CVR.


title: Mosaic and non-mosaic pcdh19 mutation leads to neuronal hyperexcitability in zebrafish

abstract: Epilepsy is one of the most common neurological disorders. The X-linked gene PCDH19 is associated with sporadic and familial epilepsy in humans, typically with early-onset clustering seizures and intellectual disability in females but not in so-called  carrier males, suggesting that mosaic PCDH19 expression is required to produce epilepsy. To characterize the role of loss of PCDH19 function in epilepsy, we generated zebrafish with truncating pcdh19 variants. Evaluating zebrafish larvae for electrophysiological abnormalities, we observed hyperexcitability phenotypes in both mosaic and non-mosaic pcdh19+/- and pcdh19-/- mutant larvae. Thus, we demonstrate that the key feature of epilepsy--network hyperexcitability--can be modeled effectively in zebrafish, even though overt spontaneous seizure-like swim patterns were not observed. Further, zebrafish with non-mosaic pcdh19 mutation displayed reduced numbers of inhibitory interneurons suggesting a potential cellular basis for the observed hyperexcitability. Our findings in both mosaic and non-mosaic pcdh19 mutant zebrafish challenge the prevailing theory that mosaicism governs all PCDH19-related phenotypes and point to interneuron-mediated mechanisms underlying these phenotypes.


title: Temporal irreversibility of neural dynamics as a signature of consciousness

abstract: Even though the fundamental laws of physics are the same when the direction of time is inverted, dissipative systems evolve in the preferred temporal direction indicated by the thermodynamic arrow of time. The fundamental nature of this temporal asymmetry led us to hypothesize its presence in the neural activity evoked by conscious perception of the physical world, and thus its covariance with the level of conscious awareness. Inspired by recent developments in stochastic thermodynamics, we implemented a data-driven and model-free deep learning framework to decode the temporal inversion of electrocorticography signals acquired from non-human primates. Brain activity time series recorded during conscious wakefulness could be distinguished from their inverted counterparts with high accuracy, both using frequency and phase information. However, classification accuracy was reduced for data acquired during deep sleep and under ketamine-induced anesthesia; moreover, the predictions obtained from multiple independent neural networks were less consistent for sleep and anesthesia than for conscious wakefulness. Finally, the analysis of feature importance scores highlighted transitions between slow ({approx}20 Hz) and fast frequencies (> 40 Hz) as the main contributors to the temporal asymmetry observed during conscious wakefulness. Our results show that a preferred temporal direction is simultaneously manifest in the neural activity evoked by conscious mentation and in the phenomenology of the passage of time, establishing common ground to tackle the relationship between brain and subjective experience.


title: Single-cell perturbation dissects transcription factor control of progression speed and trajectory choice in early T-cell development

abstract: In early T-cell development, single cells dynamically shift expression of multiple transcription factors (TFs) during transition from multipotentiality to T-lineage commitment, but the functional roles of many TFs have been obscure. Here, synchronized in vitro differentiation systems, scRNA-seq with batch indexing, and controlled gene-disruption strategies have unraveled single-cell impacts of perturbing individual TFs at two stages in early T-cell development. Single-cell CRISPR perturbation revealed that early-acting TFs Bcl11a, Erg, Spi1 (PU.1), Gata3, and Tcf7 (TCF1) each play individualized roles promoting or retarding T-lineage progression and suppressing alternative trajectories, collectively determining population dynamics and path topologies. Later, during T-lineage commitment, cells prevented from expressing TF Bcl11b  realized this abnormality not with a developmental block, but by shifting into a divergent path via bZIP and Sox TF activation as well as E protein antagonism, finally exiting the T-lineage trajectory. These TFs thus exert a network of impacts to control progression kinetics, trajectories, and differentiation outcomes of early pro-T cells.


title: The Immunomodulatory Effects of Social Isolation in Mice are Linked to Temperature Control

abstract: Living in isolation is considered an emerging societal problem that negatively affects the physical wellbeing of its sufferers in ways that we are just starting to appreciate. This study investigates the immunomodulatory effects of social isolation in mice, utilising a two-week program of sole cage occupancy followed by the testing of immune-inflammatory resilience to bacterial sepsis. Our results revealed that mice housed in social isolation showed an increased ability to clear bacterial infection compared to control socially housed animals. These effects were associated with specific changes in whole blood gene expression profile and an increased production of classical pro-inflammatory cytokines. Interestingly, equipping socially isolated mice with artificial nests as a substitute for their natural huddling behaviour reversed the increased resistance to bacterial sepsis. These results further highlight the ability of the immune system to act as a sensor of our living conditions and to respond in a compensatory fashion to external challenges that might threaten the survival of the host.


title: CROP: A Retromer-PROPPIN complex mediating membrane fission in the endo-lysosomal system

abstract: Endo-lysosomal compartments exchange proteins by fusing, fissioning, and through endosomal transport carriers. Thereby, they sort many plasma membrane receptors and transporters and control cellular signaling and metabolism. How the membrane fission events are catalyzed is poorly understood. Here, we identify the novel CROP complex as a factor acting at this step. CROP joins members of two protein families: the peripheral subunits of retromer, a coat forming endosomal transport carriers, and membrane inserting PROPPINs. Integration into CROP potentiates the membrane fission activity of the PROPPIN Atg18 on synthetic liposomes and confers strong preference for binding PI(3,5)P2, a phosphoinositide required for membrane fission activity. Disrupting CROP blocks fragmentation of lysosome-like yeast vacuoles in vivo. CROP-deficient mammalian endosomes accumulate micrometer-long tubules and fail to export cargo, suggesting that carriers attempt to form but cannot separate from these organelles. PROPPINs compete for retromer binding with the SNX proteins, which recruit retromer to the membrane during the formation of endosomal carriers. Transition from retromer-SNX complexes to retromer-PROPPIN complexes might hence switch retromer activities from cargo capture to membrane fission.

category: cell biology


title: Entry to and exit from diapause arrest in Caenorhabditis elegans are both regulated by a steroid hormone pathway

abstract:
Diapause arrest in animals such as Caenorhabditis elegans is tightly regulated so that animals make appropriate developmental decisions amidst environmental challenges. Fully understanding diapause requires mechanistic insight of both entry and exit from the arrested state. While a steroid hormone pathway regulates the entry decision into Caenorhabditis elegans dauer diapause, its role in the exit decision is less clear. A complication to understanding steroid hormonal regulation of dauer has been the peculiar fact that steroid hormone mutants such as daf-9 form partial dauers under normal growth conditions. Here, we corroborate previous findings that daf-9 mutants remain capable of forming full dauers under unfavorable growth conditions, and we establish that the daf-9 partial dauer state is likely a partially exited dauer that has initiated but cannot complete the dauer exit decision. We show that the steroid hormone pathway is both necessary for and promotes complete dauer exit, and that the spatiotemporal dynamics of steroid hormone regulation during dauer exit resembles that of dauer entry. Overall, dauer entry and dauer exit are distinct developmental decisions that are both controlled by steroid hormone signaling.

Summary StatementIn animals such as Caenorhabditis elegans, a steroid hormone pathway controls both the entry and exit decisions into and out of the developmentally arrested dauer state in response to environmental signaling.

category: developmental biology


title: An integrative approach to mosquito dynamics reveals differences in people's everyday experiences of mosquitoes

abstract:
O_LIUrban environments are heterogeneous landscapes of social and environmental features, with important consequences for human-nature entanglements, such as that of mosquito-borne disease.
C_LIO_LIInvestigations into this intra-urban heterogeneity in mosquito dynamics find conflicting results, likely due to the complex socio-ecological interactions and the importance of place-based context. Integrative research, which synthesizes multiple disciplines and epistemologies, can help place ecological results into their social context to explore these place-based differences.
C_LIO_LIHere, we develop an integrative approach to understanding spatial patterns of mosquito burdens in urban systems by combining entomological surveys, semi-structured interviews, and sketch maps.
C_LIO_LIAlthough we found no evidence for a difference in mosquito abundance across an urban gradient, there were differences in individuals everyday experiences with mosquitoes. These differences were mediated by how individuals moved through public space and their vulnerability to hazards in these spaces.
C_LIO_LIThis example of integrative research illustrates what can be gained from the inclusion of multiple epistemologies, particularly for research in socio-ecological systems.
C_LI

category: ecology


title: Do forest over- and understory respond to the same environmental variables when viewed at the taxonomic and trait level?

abstract: While the relative importance of climate filtering is known to be higher for woody species assemblages than herbaceous assemblage, it remains largely unexplored whether this pattern is also reflected between the woody overstory and herbaceous understory of forests. While climatic variation will be more buffered by the tree layer, the understory might also respond more to small-scale soil variation, next to experiencing additional environmental filtering due to the overstorys effects on light and litter quality. For (sub)tropical forests, the understory often contains a high proportion of fern and lycophyte species, for which environmental filtering is even less well understood. We explored the proportional importance of climate proxies and soil variation on the species, functional trait and (functional) diversity patterns of both the forest overstory and fern and lycophyte understory along an elevational gradient from 850 to 2100 m a.s.l. in northern Taiwan. We selected nine functional traits expected to respond to soil nutrient or climatic stress for this study and furthermore verified whether they were positively related across vegetation layers, as expected when driven by similar environmental drivers. We found that climate was a proportionally more important predictor than soil for the species composition of both vegetation layers and trait composition of the understory. The stronger than expected proportional effect of climate for the understory was likely due to fern and lycophytes higher vulnerability to drought, while the high importance of soil for the overstory seemed driven by deciduous species. The environmental drivers affected different response traits in both vegetation layers, however, which together with additional overstory effects on understory traits, resulted in a strong disconnection of community-level trait values across layers. Interestingly, species and functional diversity patterns could be almost exclusively explained by climate effects for both vegetational layers, with the exception of understory species richness. This study illustrates that environmental filtering can differentially affect species, trait and diversity patterns and can be highly divergent for forest overstory and understory vegetation, and should consequently not be extrapolated across vegetation layers or between composition and diversity patterns.


title: Molecular evolution and genetic analysis of Mesta yellow vein mosaic virus and associated betasatellites

abstract: Mesta yellow vein mosaic disease (MYVMD), one of the major diseases circulating mesta growing regions of Indian sub-continent, is responsible for serious yield loss in mesta crops. A complex of monopartite begomovirus, Mesta yellow vein mosaic virus (MYVMV) and associated betasatellite, is reported in several studies as the causal agent of MYVMD. However, all-inclusive molecular evolutionary analysis of so far available MYVMVs and associated betasatellites disseminating in this region is still lacking. In this study, by estimating and analyzing various indexes of population genetics and evolutionary parameters, we discussed the sources of genetic variations, population dynamics and different forces acting on the evolution of MYVMVs and associated betasatellites. The study finds recombination as a vital force in the evolution and diversification of begomovirus complexes in different geographic locations however, betasatellites were found to be exposed to more diverse recombination events compared to MYVMVs. Indian isolates are reported to have high frequency of polymorphism in this study which suggests a balancing selection or expansion occurring in Indian populations of begomoviruses. Higher degree of genetic differentiation and lower rate of gene flow calculated between the viral populations of Bangladesh and Pakistan is justified by the relatively far geographical distance between these two countries. Although the study detects overall purifying selection, the degrees of constraints acting on individual gene tested are found different. Coat protein (AV1) is estimated with very high nucleotide substitution rate which is very likely to result from the strongest purifying selection pressure (dN/dS = 0.131) calculated in this study on coat protein. The findings of this study on different evolutionary forces that shape the emergence and diversification of MYVMVs and associated betasatellites may provide directions towards future evolutionary trend analysis and development of comprehensive disease control strategies for begomoviruses.

category: evolutionary biology


title: Bdelloid rotifers use hundreds of horizontally acquired genes against fungal pathogens

abstract: Obligately asexual lineages are typically rare and short-lived. According to one hypothesis, they adapt too slowly to withstand relentlessly coevolving pathogens. Bdelloid rotifers seem to have avoided this fate, by enduring millions of years without males or sex. We investigated whether bdelloids unusual capacity to acquire non-metazoan genes horizontally has enhanced their resistance to pathogens. We found that horizontally transferred genes are three times more likely than native genes to be upregulated in response to a natural fungal pathogen. This enrichment was twofold stronger than that elicited by a physical stressor (desiccation), and the genes showed little overlap. Among hundreds of upregulated non-metazoan genes were RNA ligases putatively involved in resisting fungal toxins and glucanases predicted to bind to fungal cell walls, acquired from bacteria. Our results provide evidence that bdelloids mitigate a predicted challenge of long-term asexuality in part through their ability to acquire and deploy so many foreign genes.


title: Intraspecific Competition and the Promotion of Ecological Specialization

abstract: The evolution of ecological specialization can be summed up in a single question: why would a species evolve a more-restricted niche space? Various hypotheses have been developed to explain the promotion or suppression of ecological specialization. One hypothesis, competitive diversification, states that increased intraspecific competition will cause a population to broaden its niche breadth. With individuals alike in resource use preference, more individuals reduce the availability of preferred resources and should grant higher fitness to those that use secondary resources. However, recent studies cast doubt on this hypothesis with increased intraspecific competition reducing niche breadth in some systems. We present a game-theoretic evolutionary model showing greater ecological specialization with intraspecific competition under specific conditions. This is in contrast to the competitive diversification hypothesis. Our analysis reveals that specialization can offer a competitive advantage. Largely, when facing weak competition, more specialized individuals are able to acquire more of the preferred resources without greatly sacrificing secondary resources and therefore gain higher fitness. Only when competition is too great for an individual to significantly affect resource use will intraspecific competition lead to an increased niche breadth. Other conditions, such as a low diversity of resources and a low penalty to specialization, help promote ecological specialization in the face of intraspecific competition. Through this work, we have been able to discover a previously unseen role that intraspecific competition plays in the evolution of ecological specialization.


title: History-Dependent Physiological Adaptation to Lethal Genetic Modification under Antibiotic Exposure

abstract: Genetic modifications, such as gene deletion and mutations, could lead to significant changes in physiological states or even cell death. Bacterial cells can adapt to diverse external stresses, such as antibiotic exposure, but can they also adapt to detrimental genetic modification? To address this issue, we visualized the response of individual Escherichia coli cells to deletion of the antibiotic resistance gene under chloramphenicol (Cp) exposure, combining the light-inducible genetic recombination and microfluidic long-term single-cell tracking. We found that a significant fraction ([~] 40%) of resistance-gene-deleted cells demonstrated a gradual restoration of growth and stably proliferated under continuous Cp exposure without additional mutations. Such physiological adaptation to genetic modification was not observed when the deletion was introduced in 10 h or more advance before Cp exposure. Resistance gene deletion under Cp exposure disrupted the stoichiometric balance of ribosomal large and small subunit proteins (RplS and RpsB). However, the balance was gradually recovered in the cell lineages with restored growth. These results demonstrate that bacterial cells can adapt even to lethal genetic modifications by plastically gaining physiological resistance. However, the access to the resistance states is limited by the environmental histories and the timings of genetic modification.

category: genetics


title: Genome size evolution in the beetle genus Diabrotica

abstract: Diabrocite corn rootworms are one of the most economically significant pests of maize in the United States and Europe and an emerging model for insect-plant interactions. Genome sizes of several species in the genus Diabrotica were estimated using flow cytometry along with that of Acalymma vittatum as an outgroup. Genome sizes ranged between 1.56 - 1.64 gigabase pairs (Gb) and between 2.26-2.59 Gb, respectively, for the Diabrotica subgroups fucata and virgifera; the Acalymma vittatum genome size was around 1.65 Gb. This result indicated that a substantial increase in genome size occurred in the ancestor of the virgifera group. Further analysis of fucata group and virgifera group genome sequencing reads indicated that the genome size difference between the Diabrotica subgroups could be attributed to a higher content of transposable elements, mostly miniature inverted-transposable elements (MITEs) and gypsy-like long terminal repeat (LTR) retroelements.

category: genomics


title: Relationship Between Inter-individual Variation in Circadian Rhythm and Sociality: A case Study Using Halictid Bees

abstract: The bee family Halictidae is considered to be an optimal model for the study of social evolution due to its remarkable range of social behaviors. Past studies in circadian rhythms suggest that social species may express more diversity in circadian behaviors than solitary species. However, these previous studies did not make appropriate taxonomic comparisons. To further explore the link between circadian rhythms and sociality, we examine four halictid species with different degrees of sociality, three social species of Lasioglossum, one from Greece and two from Puerto Rico, and a solitary species of Systropha from Greece. Based on our previous observations, we hypothesized that species with greater degree of sociality will show greater inter-individual variation in circadian rhythms than solitary species. We observed distinct differences in their circadian behavior that parallel differences across sociality, where the most social species expressed the highest inter-individual variation. We predict that circadian rhythm differences will be informative of sociality across organisms.


title: The visual coupling between neighbors explains 'flocking' in human crowds

abstract: Patterns of collective motion or  flocking in birds, fish schools, and human crowds are believed to emerge from local interactions between individuals. Most models of collective motion attribute these interactions to hypothetical rules or forces, often inspired by physical systems, and described from an overhead view. We develop a visual model of human flocking from an embedded view, based on optical variables that actually govern pedestrian interactions. Specifically, people control their walking speed and direction by canceling the average optical expansion and angular velocity of their neighbors, weighted by visual occlusion. We test the model by simulating data from experiments with virtual crowds and real human  swarms. The visual model outperforms our previous overhead model and explains basic properties of physics-inspired models:  repulsion forces reduce to canceling optical expansion,  attraction forces to canceling optical contraction, and  alignment to canceling the combination of expansion/contraction and angular velocity. Critically, the neighborhood of interaction follows from Euclids Law of perspective and the geometry of occlusion. We conclude that the local interactions underlying human flocking are a natural consequence of the laws of optics. Similar principles may apply to collective motion in other species.


title: Allosteric cooperation in β-lactam binding to a non-classical transpeptidase

abstract: Mycobacterium tuberculosis peptidoglycan (PG) is atypical as its synthesis involves a new enzyme class, L,D-transpeptidases. Prior studies of L,D-transpeptidases have identified only the catalytic site that binds to peptide moiety of the PG substrate or {beta}-lactam antibiotics. This insight was leveraged to develop mechanism of its activity and inhibition by {beta}-lactams. Here we report identification of an allosteric site at a distance of 21 [A] from the catalytic site that binds the sugar moiety of PG substrates (hereafter referred to as the S-pocket). This site also binds a second {beta}-lactam molecule and influences binding at the catalytic site. We provide evidence that two {beta}-lactam molecules bind co-operatively to this enzyme, one non-covalently at the S-site and one covalently at the catalytic site. This dual {beta}-lactam binding phenomenon is previously unknown and is an observation that may offer novel approaches for the structure-based design of new {beta}-lactam antibiotics for M. tuberculosis.

category: biochemistry


title: DSCN: double-target selection guided by CRISPR screening and network

abstract:
Cancer is a complex disease with usually multiple disease mechanisms. Target combination is a better strategy than a single target in developing cancer therapies. However, target combinations are generally more difficult to be predicted. Current CRISPR-cas9 technology enables genome-wide screening for potential targets, but only a handful of genes have been screend as target combinations. Thus, an effective computational approach for selecting candidate target combinations is highly desirable. Selected target combinations also need to be translational between cell lines and cancer patients.

We have therefore developed DSCN (double-target selection guided by CRISPR screening and network), a method that matches expression levels in patients and gene essentialities in cell lines through spectral-clustered protein-protein interaction (PPI) network. In DSCN, a sub-sampling approach is developed to model first-target knockdown and its impact on the PPI network, and it also facilitates the selection of a second target. Our analysis first demonstrated high correlation of the DSCN sub-sampling-based gene knockdown model and its predicted differential gene expressions using observed gene expression in 22 pancreatic cell lines before and after MAP2K1 and MAP2K2 inhibition (R2 = 0.75). In our DSCN algorithm, various scoring schemes were evaluated. The  diffusion-path method showed the most significant statistical power of differentialting known synthetic lethal (SL) versus non-SL gene pairs (P = 0.001) in pancreatic cancer. The superior performance of DSCN over existing network-based algorithms, such as OptiCon[1] and VIPER[2], in the selection of target combinations is attributable to its ability to calculate combinations for any gene pairs, whereas other approaches focus on the combinations among optimized regulators in the network. DSCNs computational speed is also at least ten times faster than that of other methods. Finally, in applying DSCN to predict target combinations and drug combinations for individual samples (DSCNi), we showed high correlation of DSCNi predicted target combinations with synergistic drug combinations (P = 1e-5) in pancreatic cell lines. In summary, DSCN is a highly effective computational method for the selection of target combinations.

Author SummaryCancer therapies require targets to function. Compared to single target, target combination is a better strategy for developing cancer therapies. However, predicting target combination is much complicated than predicting single target. Current CRISPR technology enables whole genome screening of potential targets. But most of the experiments have been conducted on single target (gene) level. To facilitate the prediction of target combinations, we developed DSCN (double-target selection guided by CRISPR screening and network) that utilize single target-level CRISPR screening data and expression profiles for predicting target combinations by connecting cell-line omics-data with tissue omics-data. DSCN showed great accuracy on different cancer types and superior performance compared to existing network-based prediction tools. We also introduced DSCNi derived from DSCN and designed specific for predicting target combinations for single-paitent. We showed synergistic target combinations predicted by DSCNi accurately reflected synergies on drug combination levels. Thus, DSCN and DSCNi have the potential be further applied in personalized medicine field.

category: bioinformatics


title: ScanNet: An interpretable geometric deep learning model for structure-based protein binding site prediction

abstract: Predicting the functional sites of a protein from its structure, such as the binding sites of small molecules, other proteins or antibodies sheds light on its function in vivo. Currently, two classes of methods prevail: Machine Learning (ML) models built on top of handcrafted features and comparative modeling. They are respectively limited by the expressivity of the handcrafted features and the availability of similar proteins. Here, we introduce ScanNet, an end-to-end, interpretable geometric deep learning model that learns features directly from 3D structures. ScanNet builds representations of atoms and amino acids based on the spatio-chemical arrangement of their neighbors. We train ScanNet for detecting protein-protein and protein-antibody binding sites, demonstrate its accuracy - including for unseen protein folds - and interpret the filters learned. Finally, we predict epitopes of the SARS-CoV-2 spike protein, validating known antigenic regions and predicting previously uncharacterized ones. Overall, ScanNet is a versatile, powerful, and interpretable model suitable for functional site prediction tasks. A webserver for ScanNet is available from http://bioinfo3d.cs.tau.ac.il/ScanNet/