title: Markov chains improve the significance computation of overlapping genome annotations

abstract:
MotivationGenome annotations are a common way to represent genomic features such as genes, regulatory elements or epigenetic modifications. The amount of overlap between two annotations is often used to ascertain if there is an underlying biological connection between them. In order to distinguish between true biological association and overlap by pure chance, a robust measure of significance is required. One common way to do this is to determine if the number of intervals in the reference annotation that intersect the query annotation is statistically significant. However, currently employed statistical frameworks are often either inefficient or inaccurate when computing p-values on the scale of the whole human genome.

ResultsWe show that finding the p-values under the typically used "gold" null hypothesis is[N][P] -hard. This motivates us to reformulate the null hypothesis using Markov chains. To be able to measure the fidelity of our Markovian null hypothesis, we develop a fast direct sampling algorithm to estimate the p-value under the gold null hypothesis. We then present an open-source software tool MCDP that computes the p-values under the Markovian null hypothesis in[O] (m2 + n) time and[O] (m) memory, where m and n are the numbers of intervals in the reference and query annotations, respectively. Notably, MCDP runtime and memory usage are independent from the genome length, allowing it to outperform previous approaches in runtime and memory usage by orders of magnitude on human genome annotations, while maintaining the same level of accuracy.

AvailabilityThe software is available at https://github.com/fmfi-compbio/mc-overlaps. All data for reproducibility are available at https://github.com/fmfi-compbio/mc-overlaps-reproducibility


title: FollicleFinder: automated three-dimensional segmentation of human ovarian follicles

abstract:
In vitro fertilization (IVF) treatment protocols require frequent monitoring of the ovarian follicle growth process. We report FollicleFinder, an open source pipeline for the automated, 3D segmentation of ovarian follicles. FollicleFinder also accurately measures clinically-relevant morphological properties such as diameter, surface area, and volume.

AvailabilityThe FollicleFinder pipeline is available at https://git.bsse.ethz.ch/iber/ovary-analysis and the graphical user interface is available at https://git.bsse.ethz.ch/iber/follicle-tracker.

category: bioinformatics


title: Genomic analyses identify key molecules and significant biological processes in LOC441461 treated gastric cancer cells

abstract: Gastric cancer (GC) remains one of the leading cancers globally with a high prevalence and high mortality rate. Currently, Long noncoding RNAs (lncRNAs) LOC441461 have been found to be related to cancer that regulates cell growth, apoptosis, and metastasis. However, the mechanisms of LOC441461 treated gastric cancer are still unknown. In this study, we aim to identify the key molecules and signaling pathways by analyzing the RNA-seq data. The GSE193700 was created by the Illumina NovaSeq 6000 (Homo sapiens). The KEGG and GO analyses indicated that Human papillomavirus infection and Epstein-Barr virus infection were the main biological processes during the knockdown of LOC441461 in gastric cancer. Moreover, we figured out several interactive genes including STAT1, IFIH1, ISG15, IRF7, IRF1, MX1, DDX58, IFIT1, RSAD2, and IFIT3. Our study may provide new knowledge on the treatment of gastric cancer.


title: AURTHO: autoregulation as facilitator of cis-acting element discovery of orthologous transcription factors

abstract:
Transcriptional regulation is key in bacteria for providing an adequate response in time and space to changing environmental conditions. However, despite decades of research, the binding sites and therefore the target genes and the function of most transcription factors (TFs) remain unknown. Filling this gap in knowledge through conventional methods represents a colossal task which we demonstrate here can be significantly facilitated by a widespread feature in transcriptional control: the autoregulation of TFs implying that the yet unknown transcription factor binding site (TFBS) is neighbouring the TF itself. In this work, we describe the "AURTHO" methodology (AUtoregulation of oRTHOlogous transcription factors), consisting of analyzing upstream regions of orthologous TFs in order to uncover their associated TFBSs. AURTHO enabled the de novo identification of novel TFBSs with an unprecedented improvement in terms of quantity and reliability. DNA-protein interaction studies on a selection of candidate cis-acting elements yielded an >90% success rate, demonstrating the efficacy of AURTHO at highlighting true TF-TFBS couples and confirming the identification in a near future of a plethora of TFBSs across all bacterial species.

Key pointsO_LITranscription factor (TF) autoregulation implies that their binding site (TFBS) is in their close vicinity
C_LIO_LIWe developed and assessed the AURTHO methodology (AUtoregulation of oRTHOlogous TFs) for TFBS discovery
C_LIO_LIOur results shows that AURTHO greatly facilitates the identification of highly reliable novel TFBSs
C_LI


title: Targeting RNA:Protein Interactions with an Integrative Approach Leads tothe Identification of Potent YB-1 Inhibitors

abstract: RNA-binding proteins are promising targets for developing new molecules of therapeutic interest. Nevertheless, targeting RNA:Protein interfaces is hampered by the lack of methods able to detect these interactions in cells while being amenable to High Content Screening. Here, we adapt the microtubule bench assay to score small molecules targeting interactions of endogenous mRNA with a specific protein in cells and demonstrate its robustness by targeting YB-1 (YBX-1 gene), a mRNA-binding protein involved in cancer progression and resistance to chemotherapy. The implementation of an integrative approach led to the identification of 22 hits validated by NMR and MD simulations of which 11 were found to significantly interfere with the binding of mRNA to YB-1 in cells at low micromolar concentrations. One of our leads is P1, an FDA-approved PARP-1 inhibitor. This work shows the potential of our integrative approach and paves the way for the development of RNA:Protein Interaction inhibitors.

category: biophysics


title: Genome-wide analysis reveals PhoP regulates pathogenicity in Riemerella anatipestifer

abstract:
Duck infectious serositis, also known as the Riemerella anatipestifer disease infects domestic ducks, geese, turkeys, and wild birds. However, the regulatory mechanism of its pathogenicity remains unclear. The phoP/phoR two-component system was first reported in gram-negative bacteria in our previous research and was demonstrated to be involved in virulence and gene expression. Here, the DNA-affinity-purified sequencing (DAP-seq) was applied to further explore the regulation of phoP/phoR to pathogenicity in R. anatipestifer. A conserved motif was identified in the upstream of 583 candidate target genes which were directly regulated by phoP. To further confirm the genes which are regulated by phoP/phoR, phoR and phoP, the single-gene deletion strains were constructed. The results of transcriptome analysis using next-generation RNA sequencing showed 136 differential expression genes (DEGs) between {Delta}phoP and RA-YM, and 183 DEGs between {Delta}phoR and WT. The candidate target genes of PhoP were further identified by combining transcriptome analysis and DAP-seq. The results of DAP-seq and RNA-seq of {Delta}phoP in combination revealed that the main direct regulons of PhoP are located on the membrane and PhoP is involved in regulating aerotolerance. Using the in vivo duck model, the pathogenicity of {Delta}phoP or {Delta}phoR was significantly lower than that of the WT. Together, our findings provided a perception about the direct regulation of PhoP and suggested that phoP/phoR is essential for the pathogenicity of R. anatipestifer, and phoP/phoR is related to the aerotolerance of R. anatipestifer. The gene deletion strains are expected to be the candidate live vaccine strains of R. anatipestifer which can be used as ideal genetic engineering vector strains for the expression of foreign antigens.

Author summaryRiemerella anatipestifer is a severe pathogen in the poultry industry with high mortality in ducks and geese mainly due to acute septicemia and infectious polyserositis. A two-component system phoP/phoR was previously characterized in R. anatipestifer, and the phoP/phoR TCS was reported for the first time in Gram-negative bacteria. A deleted phoP/phoR in R. anatipestifer has been reported to almost lose its pathogenicity in ducklings. However, the mechanism of phoP/phoR regulating the virulence of R. anatipestifer had not been explored in detail. This study has utilized DAP-seq to explore the DNA-binding sites of PhoP as a response regulator in the global genome. Furthermore, the phoP and phoR were deleted separately and the transcriptomics of the corresponding gene-deleted strains was analyzed. A series of directly regulated genes of phoP/phoR TCS were determined in combination. The duckling model revealed both PhoP and PhoR as essential virulence-related factors of R. anatipestifer.

category: pathology


title: The phosphoproteome is a first responder in tiered cellular adaptation to chemical stress followed by proteomics and transcriptomics alteration

abstract: Next-generation risk assessment for environmental chemicals and ingredients in consumer products involves a weight of evidence (WoE) framework integrating a suite of new approach methodologies (NAMs) based on points of departure (PoD) obtained from in vitro assays. Omics techniques provide broad coverages of the molecular toxicity pathway space. Transcriptomics assays especially play a leading role by providing relatively conservative PoDs in comparison with apical endpoints. However, it is unclear whether and how parameters measured using other omics technicquesparticipate in the cellular response to chemical perturbations, especially at exposure levels below the transcriptomically defined PoD. Multi-omics coverage may provide additional sensitive or confirmative biomarkers to complement and reduce the uncertainty in safety decisions made using targeted and transcriptomics assays. In the present study, we compared changes in transcriptomics, proteomics and phosphoproteomics with two prototype compounds, coumarin, as a main study and doxorubicin, as a complementary study to understand the sensitivity of the three omics techniques in response to chemically-induced changes in HepG2 and AC16 cells. With measurements obtained for multiple chemical concentrations and time points, we demonstrated that, compared with proteomics and transcriptomics, phosphoproteomics alterations occur not only earlier in time as expected, but also at much lower chemical concentrations and hence are proximal to the very early effects induced by chemical exposure. The phosphoproteomics changes appear to approach maximum when the transcriptomics alterations begin to be initiated. The results are consistent with a tiered framework of cellular response to chemical insults, where posttranslational modification of preexisting proteins is first seen before transcriptomics induction is engaged to launch a more energy-expensive defense that defines a useful PoD. We conclude that as the cost becomes more affordable, proteomics covering posttranslational modifications can be utilized to provide a more complete coverage of chemical-induced cellular alteration and supplement transcriptomics-based health safety decision making.

category: pharmacology and toxicology


title: A six-months, long acting, one-shot injectable formulation of Ivermectin as a complementary malaria vector control tool to target zoophagic Anopheles : laboratory and model-based proofs of concept.

abstract:
ContextIn the current context of residual plasmodium transmission where zoophagic proclivities of Anopheles intervene, we propose to treat peridomestic animals using the endectocide Ivermectin as a complementary approach to bednets. As Ivermectin remanence with classic veterinary compounds is insufficient to induce a significant decrease in vectors populations, we developed a long-lasting injectable formulation of ivermectin from the BEPO(R) technology designed to release insecticidal concentrations of the molecule for 6 months. The work reported here is a proof of concept that using this new technology could help decrease field Anopheles populations.

MethodsEight calves were injected with Ivermectin therapeutic doses of 1.2 mg/kg body weight using 2 long lasting formulations (A and B). Efficacy of the product at killing wild derived An. coluzzii has been evaluated by direct-skin feeding assays from 1 to 210 days after injection (DAI). Efficacy on survival was estimated with Cox proportional hazards mixed models and Kaplan meier estimates. To predict efficacy in field-based scenarii, we used a transmission model fed with an entomological model considering different levels for the Anopheles zoophagic preference, calves vs humans ratios, and bed net use variables.

ResultsThe release at mosquitocidal plasmatic concentrations of Ivermectin during 6 months is confirmed for both formulations (Hazard ratios > 1 for both formulations against their vehicle for 210 days). The Ivermectin concentration allowing to kill 90% of the mosquitoes before the extrinsic incubation period of the parasite is achieved (10 days) are 11 and 9 ng/ml for formulations A and B if the blood meal is taken before the infectious one, and 15 and 13 ng/ml if it was taken after. Modeling showed that Ivermectin treatment of calves using BEPO(R) technology would reduce infectious vector populations, from at least 35% for most anthropophagic Anopheles in villages where cattle to human ratio is the lowest, to more than 75% if vectors were zoophagic and calves numbers superior to humans.

ConclusionOur study gives the proof of concept that a long-lasting formulation of Ivermectin administered to calves could help decrease field malaria vectors populations, which may, ultimately, have an impact at the epidemiological level.


title: Liver-secreted fluorescent blood plasma markers enable chronic imaging of microcirculation

abstract: Studying blood microcirculation is vital for gaining insights into vascular diseases. Acute administration of fluorescent tracers is currently used for deep tissue blood flow imaging. This is invasive, and the plasma fluorescence decreases within an hour of administration. We report a novel approach for the longitudinal study of vasculature. Using a single systemic administration of viral vectors, we express fluorescent secretory albumin-fusion proteins in the liver to label the blood in mice. All segments of the vasculature in brain and peripheral tissue are observable by two-photon microscopy within two weeks of vector administration. This approach allows for observation of circulation without the need for repeated administration for several months. We demonstrate the chronic assessment of vascular functions at micro-and mesoscopic scales. This genetic plasma labeling approach represents a versatile and cost-effective method for the chronic investigation of vasculature functions across the body in health and disease.

category: physiology


title: The PAICE Suite Reveals Circadian Post-Transcriptional Timing of Non-Coding RNAs and Spliceosome Components in Mus musculus Macrophages

abstract: Circadian rhythms broadly regulate physiological functions by tuning oscillations in the levels of mRNAs and proteins to the 24-hour day/night cycle. Globally assessing which mRNAs and proteins are timed by the clock necessitates accurate recognition of oscillations in RNA and protein data, particularly in large omics data sets. Tools that employ fixed-amplitude models have previously been used to positive effect. However, the recognition of amplitude-change in circadian oscillations required a new generation of analytical software to enhance the identification of these oscillations. To address this gap, we created the Pipeline for Amplitude Integration of Circadian Exploration (PAICE) suite. Here, we demonstrate the PAICE suites increased detection of circadian trends through the joint modeling of the Mus musculus macrophage transcriptome and proteome. Our enhanced detection confirmed extensive circadian post-transcriptional regulation in macrophages, but highlighted that some of the reported discrepancy between mRNA and protein oscillations was due to noise in data. We further applied the PAICE suite to investigate the circadian timing of non-coding RNAs, documenting extensive circadian timing of long non-coding RNAs and small nuclear RNAs, which control the recognition of mRNA in the spliceosome complex. By tracking oscillating spliceosome complex proteins using the PAICE suite, we noted that the clock broadly regulates the spliceosome, particularly the major spliceosome complex. As most of the above-noted rhythms had damped amplitude changes in their oscillations, this work highlights the importance of the PAICE suite in the thorough enumeration of oscillations in omics-scale datasets.

category: systems biology


title: Multi-modal deep neural decoding of visual object representation in humans

abstract: Perception and categorization of objects in a visual scene are essential to grasp the surrounding situation. However, it is unclear how neural activities in spatially-distributed brain regions, especially in the aspect of temporal dynamics, represent visual objects. To address this issue, we explored spatial and temporal organization of visual object representations using concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), combined with neural decoding by deep neural networks (DNNs). Visualization of the fMRI DNN revealed that visual categorization (faces or non-face objects) occurred in brain-wide cortical regions, including the ventral temporal cortex. Interestingly, the EEG DNN valued the earlier phase of neural responses for categorization and the later phase of neural responses for sub-categorization. Combination of both DNNs improved classification performance for both categorization and sub-categorization. These deep learning-based results demonstrate a categorization principle in which visual objects are represented in a spatially organized and coarse-to-fine manner.

category: neuroscience


title: Can neurogenesis act as a neural regularizer?

abstract:
New neurons are continuously generated in the subgranular zone of the dentate gyrus throughout adulthood. These new neurons gradually integrate into hippocampal circuits, forming new naive synapses. Viewed from this perspective, these new neurons may represent a significant source of  wiring noise in hippocampal networks. In machine learning, such noise injection is commonly used as a regularization technique. Regularization techniques help prevent overfitting training data, and allow models to generalize learning to new, unseen data. Using a computational modeling approach, here we ask whether a neurogenesis-like process similarly acts as a regularizer, facilitating generalization in a category learning task. In a convolutional neural network (CNN) trained on the CIFAR-10 object recognition dataset, we modeled neurogenesis as a replacement/turnover mechanism, where weights for a randomly chosen small subset of neurons in a chosen hidden layer were re-initialized to new values as the model learned to categorize 10 different classes of objects. We found that neurogenesis enhanced generalization on unseen test data compared to networks with no neurogenesis. Moreover, neurogenic networks either outperformed or performed similarly to networks with conventional noise injection (i.e., dropout, weight decay, and neural noise). These results suggest that neurogenesis can enhance generalization in hippocampal learning through noise-injection, expanding on the roles that neurogenesis may have in cognition.

Author SummaryIn deep neural networks, various forms of noise injection are used as regularization techniques to prevent overfitting and promote generalization on unseen test data. Here, we were interested in whether adult neurogenesis- the lifelong production of new neurons in the hippocampus- might similarly function as a regularizer in the brain. We explored this question computationally, assessing whether implementing a neurogenesis-like process in a hidden layer within a convolutional neural network trained in a category learning task would prevent overfitting and promote generalization. We found that neurogenesis regularization was as least as effective as, or more effective than, conventional regularizers (i.e., dropout, weight decay and neural noise) in improving model performance. These results suggest that optimal levels of hippocampal neurogenesis may improve memory-guided decision making by preventing overfitting, thereby promoting the formation of more generalized memories that can be applied in a broader range of circumstances. We outline how these predictions may be evaluated behaviorally in rodents with altered hippocampal neurogenesis.


title: mulEEG: A Multi-View Representation Learning on EEG Signals

abstract: Modeling effective representations using multiple views that positively influence each other is challenging, and the existing methods perform poorly on Electroencephalogram (EEG) signals for sleepstaging tasks. In this paper, we propose a novel multi-view self-supervised method (mulEEG) for unsupervised EEG representation learning. Our method attempts to effectively utilize the complementary information available in multiple views to learn better representations. We introduce diverse loss that further encourages complementary information across multiple views. Our method with no access to labels, beats the supervised training while outperforming multi-view baseline methods on transfer learning experiments carried out on sleep-staging tasks. We posit that our method was able to learn better representations by using complementary multi-views.{dagger}


title: The molecular mechanism and physiological role of silent nociceptor activation

abstract: Silent nociceptors are sensory afferents that are insensitive to noxious mechanical stimuli under normal conditions but become sensitized to such stimuli during inflammation. Using RNA-sequencing and quantitative RT-PCR we demonstrate that inflammation selectively upregulates the expression of the transmembrane protein TMEM100 in silent nociceptors and electrophysiology revealed that over-expression of TMEM100 is required and sufficient to un-silence silent nociceptors. Moreover, we show that mice lacking TMEM100 do not develop secondary hyperalgesia - i.e. pain hypersensitivity that spreads beyond the site of inflammation - in a mouse model of knee joint inflammation and that AAV-mediated overexpression of TMEM100 in articular afferents in the absence of inflammation is sufficient to induce secondary hyperalgesia in remote skin regions without causing knee joint pain. Thus, our work identifies TMEM100 as a key regulator of silent nociceptor un-silencing and reveals a physiological role for this hitherto enigmatic afferent subclass in triggering spatially remote secondary hyperalgesia during inflammation.


title: Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

abstract: Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2*), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2* at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.


title: Recalibrating vision-for-action requires years after sight restoration from congenital blindness

abstract: Being able to perform goal-directed actions requires predictive, feed-forward control, including a mapping between the visually estimated target locations and the motor commands reaching for them. When the mapping is perturbed, e.g., due to muscle fatigue or optical distortions, we are quickly able to recalibrate the sensorimotor system to update this mapping. Here we investigated whether early visual and visuomotor experience is essential for developing the ability to recalibrate. To this end, we assessed young individuals deprived from vision due to dense congenital bilateral cataracts, who were surgically treated for sight restoration only years after birth. We compared their recalibration performance to such distortion to that of age-matched sighted controls. Their recalibration performance was impaired right after surgery. This finding cannot be explained by their still lower visual acuity, since blurring vision in controls to a matching degree did not lead to comparable behavior. Nevertheless, the recalibration ability of cataract-treated participants improved with experience, matching controls performance after around 2 years from surgery. Thus, the lack of early visual experience affects visuomotor recalibration. However, this ability is not lost but slowly develops after sight restoration, highlighting the importance of sensorimotor experience for brain plasticity late in life.


title: Brain-wide sensory aberrations in a Parkinson's Disease mouse model revealed by functional MRI

abstract:
Parkinsons disease (PD) is associated with irreparable damage to dopaminergic neurons in brain areas involved in movement. Frequently, a very early symptom of PD involves an impaired sense of smell, while other studies suggest a broader impairment of other sensory modalities. Still, the associated brain-wide mechanisms underlying this phenomenon remain unclear. Here, we harness in vivo functional Magnetic Resonance Imaging (fMRI) at 9.4T to investigate how the olfactory and visual systems are affected in an -Synuclein (Syn) mouse model of PD. We find significant aberrations in fMRI responses along both sensory pathways including decreases in activation extent and in activation amplitude. Deficits in the olfactory system were larger than in the visual pathway, but nevertheless both sensory systems were clearly impacted, suggesting a more overarching mechanism may be involved. To further ensure that the aberrations observed in the fMRI signals were not driven solely by putative vascular deficiency, we quantified c-FOS expression in the olfactory system and found statistically significant decreases in the PD group when compared to age-matched controls. Hence, our findings indicate a neural origin for the observed fMRI aberrations. Our findings thus demonstrate a more global deficiency in sensory systems in the (Syn) mouse model.

One Sentence SummaryParkinsons disease (PD) is associated with an impaired sense of smell and more generally sensory deficits, but the associated brain-wide mechanisms remain unclear; here, we investigate aberrations in BOLD-fMRI responses along sensory pathways in an SYN PD mouse model.


title: On demand nanoliter sampling probe for collection of brain fluid

abstract:
Continuous fluidic sampling systems allow collection of brain biomarkers in vivo. Here, we propose a new sampling paradigm, Droplet on Demand (DoD), implemented in a microfabricated neural probe. It allows sampling droplets loaded with molecules from the brain extracellular fluid punctually, without the long transient equilibration periods typical of continuous methods. It uses an accurate fluidic sequence and correct operation is verified by the embedded electrodes. As a proof of concept, we demonstrated the application of this novel approach in vitro and in vivo, to collect glucose in the brain of mice, with a temporal resolution of 1-2 minutes and without transient regime. Absolute quantification of the glucose level in the samples was performed by direct infusion nanoelectrospray ionization Fourier transform mass spectrometry (nanoESI-FTMS). By adjusting the diffusion time and the perfusion volume of DoD, the fraction of molecules recovered in the samples can be tuned to mirror the tissue concentration at accurate points in time. This makes quantification of biomarkers in the brain possible within acute experiments of only 20 to 120 minutes. DoD provides a complementary tool to continuous microdialysis and push-pull sampling probes. The advances allowed by DoD will benefit quantitative molecular studies in the brain, namely for molecules involved in volume transmission or for protein aggregates that form in neurodegenerative diseases over long periods.

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title: Beyond control: experimental control protocol slightly affects prepubescent mice behavior in a sex-specific manner

abstract: Study design and experimental tools are crucial for good quality science, and an important part of it is the choice of control groups to best test the hypothesis. Two of the most common control groups in research are needle prickling without substance injection (Sham) and/or vehicle injection (Saline). Very few studies investigated the behavioral effects of a single intraperitoneal (i.p) Sham and/or single i.p. Saline administration in mice, mostly using adult males. In this study, we investigated if a single i.p. Sham and/or i.p. Saline administration affects female and male prepubertal (4-weeks-old) mice behavior. After Sham or Saline injection, we examined exploratory/motor behavior (open field test - OFT), anxiety-like behavior (elevated plus-maze - EPM), and behavioral despair/depressive-like behavior (forced swimming test - FST). We observed that both Sham prepubertal females and males showed minor behavioral alterations in OFT and EPM, and Saline males showed behavioral alterations in OFT and FST. On the other hand, prepubertal Saline females showed an increase in exploratory behavior, risk assessment/anxiety-like behavior, and behavioral despair/depressive-like behavior. Thus, we observed that the experimental procedures used as control have mild (but not insignificant) consequences on prepubescent mice behavior. However, the consequences of control protocols in prepubescent females are stronger than in males. To the best of our knowledge, this is the first study investigating the consequences of Sham and Saline protocols in prepubertal mice. This study highlights how important is to include Naive animals (Negative control) together with Sham and/or Vehicle for a better and more honest interpretation of the data.


title: Unmasking hidden changes in intrinsic properties in neurons that coordinate oscillatory networks

abstract:
2.Neurons utilize gain control to efficiently encode shifting inputs with maximum sensitivity. While gain control is present in a multitude of neurons, research on the underlying mechanisms is still sparse. We focused on one coordinating neuron (ASCE) in the crayfish swimmeret system that is both necessary and sufficient to coordinate distributed motor circuits. This neuron encodes properties of the motor activity in its home ganglion and sends the information as burst of spikes to its anterior target ganglia. Previous research has shown that ASCE encodes the strength of the motor activity by its spike number, and that the range of the number of spikes per burst adapts to the average motor activity. In turn, the motor activity can be activated and modulated via cholinergic pathways.

We explored ASCEs response to changing levels of motor system excitation, which was induced with cholinergic agonists, both when the neuron was part of the full swimmeret systems circuit and when it was isolated from the network. The cholinergic agonist carbachol directly depolarized ASCEs membrane potential via nicotinic receptors when the neuron was isolated. In the intact circuit, ASCEs membrane potential did not change but its input resistance decreased. This indicated an additional indirect action of carbachol, presumably via presynaptic central pattern generating neurons at the core of each motor circuit. The balance of direct and indirect effects could allow ASCE to match its spiking range to the systems excitation level.

1. Summary statementA balance of direct and indirect cholinergic effects precisely controls the membrane potential, and therefore the gain, of a neuron that is involved in the coordination of distributed motor circuits.


title: Hippocampal hypothyroidism in mice promotes glial cell activation and spatial memory deficits.

abstract: Adult-onset hypothyroidism is associated with learning and cognitive dysfunctions, which may be related to alterations in synaptic plasticity. Local reduced levels of thyroid hormones (THs) may impair glia morphology and activity, and promote the increase of pro-inflammatory cytokine levels mainly in the hippocampus. Given that neuroinflammation induces memory impairments, hypothyroidism-related glia dysfunction may participate in brain disorders. Thus, we investigated the mechanisms linking hypothyroidism, neuroinflammation and spatial memory, from a protective prospective. We induced hypothyroidism in adult C57BL/6J and wild-derived WSB/EiJ male mice by a seven-week propylthiouracil (PTU) treatment. We previously showed that WSB/EiJ mice were resistant to high-fat diet (HFD)-induced obesity, showing no neuroinflammatory response through adaptive abilities, unlike C57BL/6J. As PTU and HFD treatments are known to induce comparable inflammatory responses, we hypothesized WSB/EiJ mice might also be protected against hypothyroidism-induced neuroinflammation. We showed that hypothyroid WSB/EiJ mice depicted no hippocampal neuroinflammatory response and were able to maintain their hippocampal thyroid signalling despite low circulating TH levels. In contrast, C57BL/6J mice exhibited disturbed hippocampal TH signalling, accompanied by neuroinflammation and memory impairment. Our results reinforce the preponderance of local TH levels over circulating levels and the major role of hippocampal glia reactivity in the establishment of memory deficits.


title: Visuomotor mismatch responses as a hallmark of explaining away in causal inference

abstract: How are visuomotor mismatch responses in visual cortex embedded into cortical processing? We here argue that mismatch responses are best understood as the result of a cooperation of motor and visual areas to jointly explain optic flow. This cooperation ensures that optic flow is not explained redundantly by both areas, which in the language of causal inference is termed explaining away. This improves the efficiency of the resulting neural code, and allows the animal to easily detect movements that are independent of its own locomotion. We demonstrate the emergence of mismatch responses from explaining away in simulations, where spiking neurons learn to encode optic flow stimuli and locomotion. We furthermore lay out arguments against the prevailing idea that mismatch signals are the result of a dedicated error computation in a hierarchical model. These results provide a new perspective on several recent experiments of cross-modal neural interactions in cortex.


title: Genetically defined nucleus incertus neurons differ in connectivity and function

abstract: The nucleus incertus (NI), an understudied hindbrain structure implicated in the stress response, arousal, and memory, is a major site for production of the neuropeptide relaxin-3. On the basis of goosecoid homeobox 2 (gsc2) expression, we identified a neuronal cluster that lies adjacent to relaxin 3a (rln3a) neurons in the zebrafish analogue of the NI. To delineate properties of the gsc2 and rln3a neurons, we used CRISPR/Cas9 targeted integration to drive gene expression in each group, and showed that they differ in afferent input, efferent connections and functional properties. gsc2 and rln3a NI neurons innervate distinct subregions of the interpeduncular nucleus (IPN), but only gsc2 neurons receive reciprocal innervation from the IPN. Whereas gsc2 neurons are activated by electric shock, rln3a neurons exhibit spontaneous fluctuations in calcium signaling and regulate locomotor activity. Our findings define heterogeneous neurons in the NI and provide new tools to probe its diverse functions.


title: Flexible Intentions in the Posterior Parietal Cortex: An Active Inference Theory

abstract: We present a normative computational theory of how neural circuitry in the Dorsal Visual Stream (DVS) and the Posterior Parietal Cortex (PPC) support visually guided goal-directed actions in a dynamical environment through flexible goal-encoding intentions. It builds on Active Inference, in which perception and motor control signals are inferred through dynamic minimization of generalized prediction errors. The PPC is proposed to maintain a belief over bodily state and relevant objects on the scene, and by manipulating these states, it is involved along with visual, frontal, and motor areas in dynamically generating goal-directed actions including motor planning and movement control. Specifically, the PPC is viewed as a dynamic system computing flexible motor intentions and directing belief over the latent body state towards dynamic future goals, while the DVS is viewed as a generative model translating beliefs into visual sensory predictions in order to infer targets and posture. An intention-driven Active Inference agent that embodied an actuated upper limb with visual and proprioceptive sensors was able to perceive and reach visual targets, behaving correctly under various conditions, including static and dynamic targets, different sensory feedback, sensory precisions, intention gains, and movement policies. The theory is of general interest because it provides a normative basis for a variety of neurophysiological investigations of flexible goal-directed behavior and sensorimotor processes in end-to-end settings and further advances Artificial Intelligence methods for sensorimotor control.


title: Mechanisms of human dynamic object recognition revealed by sequential deep neural networks

abstract: Humans recognize objects in a dynamically changing world integrating evidence across a vast variety of timescales. This ability is showcased by performance on rapid serial visual presentation (RSVP) tasks in which observers succeed at recognizing objects in rapid sequences of natural scenes, at up to 13 ms/image. To date, the computational mechanisms governing such dynamic object recognition remain poorly understood. Here, we developed deep learning models for dynamic recognition and compared different computational mechanisms, contrasting feedforward and recurrent, single and sequential image processing as well as different forms of adaptation. We found that only models that integrate images sequentially via lateral recurrence mirrored human performance (N=36) across different image durations (13-80 ms/image). Augmenting this model with a power-law adaptation mechanism was essential for predicting human trial-by-trial reports across image durations. These findings shed new insights into the mechanisms rendering object recognition so fast and effective in a dynamic visual world.


title: Brain resident memory T cells rapidly expand and initiate neuroinflammatory responses following CNS injury and viral infection

abstract:
The contribution of circulating verses tissue resident memory T cells (TRM) to clinical neuropathology is an enduring question due to a lack of mechanistic insights. The prevailing view is TRM cells are protective against pathogens in the brain. However, the extent antigen-specific TRM cells can induce neuropathology upon reactivation has not been determined. Using the described phenotype of TRMs, we found that brains of naive mice harbor populations of CD69+ CD103- T cells. Notably, numbers of CD69+ CD103- TRM cells rapidly increase following neurological insults of physical, cancerous, or viral origins. This TRM expansion precedes infiltration of virus specific CD8 T cells and is due to proliferation of T cells within the brain. In contrast, the CD69+ CD103+ TRMs in the brain are generated after the initial expansion of CD69+ CD103- cells following injury and are antigen-specific. We next evaluated the capacity of antigen-specific TRMs in the brain to induce significant neuroinflammation post virus clearance, including infiltration of inflammatory monocytes, activation of T cells in the brain, and significant blood brain barrier disruption. These neuroinflammatory events were induced by TRMs, as depletion of peripheral T cells or blocking T cell trafficking using FTY720 did not change the neuroinflammatory course. Reactivation of antigen-specific TRMs in the brain also induced profound lymphopenia within the blood compartment. We have therefore determined that antigen-specific TRMs can induce significant neuroinflammation, neuropathology, and peripheral immune suppression. Importantly, understanding functions of brain TRMs is crucial in investigating their role in neurodegenerative disorders, CNS cancers, and long-term complications associated with viral infections including COVID-19.

Graphical AbstractHealthy brain harbors populations of resident memory T cells (TRM). These TRM cells rapidly proliferate in response to CNS insults of various origins. Following clearance of the insult, populations of TRM cells in the brain decline, but an antigen-specific TRM subset remains within the brain. Antigen-specific reactivation of brain TRMs mediates neuroinflammatory sequalae involving activation and blasting of resident T cells, infiltration of inflammatory monocytes and blood brain barrier disruption. Severe neuroinflammation within the brain following antigen-specific TRM reactivation is concurrent with profound lymphopenia within the blood compartment.

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category: immunology


title: Mathematical Modeling of Rhesus Cytomegalovirus (RhCMV) Placental Transmission in Seronegative Rhesus Macaques

abstract:
Approximately 1 in 200 infants is born with congenital cytomegalovirus (CMV), making it the most common congenital infection. About 1 in 5 congenitally-infected babies will suffer long-term sequelae, including sensorineural deafness, intellectual disability, and epilepsy. CMV infection is highly species-dependent, and the Rhesus CMV (RhCMV) infection of rhesus monkey fetuses is the only animal model that replicates essential features of congenital CMV infection in humans, including placental transmission, fetal disease, and fetal loss. To better understand the determinants and dynamics of congenital CMV transmission, we developed a mathematical model for placental transmission, comprising of maternal, placental, and fetal compartments using parameters from literature and experimental data from RhCMV seronegative rhesus macaques inoculated with RhCMV at 7.7-9.0 weeks of pregnancy. The model was then used to study the effect of the timing of inoculation, maternal immune suppression, and hyper-immune globulin infusion on the risk of placental transmission in the context of primary and reactivated chronic maternal CMV infection.

Author summaryCongenital cytomegalovirus (CMV) is the most common congenital infection in humans. Congenial CMV affects 1 in 200 infants, and can result in sensorineural deafness, intellectual disability, epilepsy, and death. The Rhesus CMV (RhCMV) model is the only animal model that replicates essential features of congenital CMV infection and fetal sequelae in humans and provides a critical experimental system to develop mechanistic insight. We propose a novel mathematical model for CMV transmission that integrates viral dynamics in the maternal, placental, and fetal compartments. We calibrate the model using data from RhCMV transmission experiments and show that the model can recapitulate experimental observations of primary versus reactivated chronic CMV infection in pregnancy, primary infection at different stages in pregnancy, and infection in the presence of varying degrees of immune suppression and hyper-immune globulin infusion. Our in-silico model provides a means to rapidly explore mechanistic hypotheses for the physical, viral, and immune determinants of CMV transmission to complement and support expensive and difficult experiments on non-human primates.


title: Humans have distinct repertoires of IgA1

abstract: The most abundant immunoglobulin present in the human body is IgA1. It has the highest concentrations at the mucosal lining and in biofluids such as milk and is the second most abundant class of antibodies in serum. We assessed the structural diversity and clonal repertoire of IgA1-containing molecular assemblies longitudinally in human serum and milk from three donors using a mass spectrometry-based approach. IgA-containing molecules purified from serum or milk were assessed by the release and subsequent analysis of their Fab fragments. Our data revealed that serum IgA1 consists of two distinct structural populations, namely monomeric IgA1 ([~] 80%) and dimeric joining (J-) chain coupled IgA1 ([~] 20%). Also, we confirmed that IgA1 in milk is present solely as secretory (S)IgA, consisting of two ([~] 50%), three ([~] 33%) or four ([~] 17%) IgA1 molecules assembled with a J-chain and secretory component (SC). Interestingly, the serum and milk IgA1-Fab repertoires were distinct between monomeric, and J-chain coupled dimeric IgA1. The serum dimeric J-chain coupled IgA1 repertoire contained several abundant clones also observed in the milk IgA1 repertoire. The latter repertoire had little to no overlap with the serum monomeric IgA1 repertoire. This suggests that human IgA1s have (at least) two distinct origins; one of these produces dimeric J-chain coupled IgA1 molecules, shared in human serum and milk, and another produces monomeric IgA1 ending up exclusively in serum.


title: Human Platelet Lysate as Alternative of Fetal Bovine Serum for Enhanced Human in vitro Bone Resorption and Remodeling

abstract: To study human physiological and pathological bone remodeling while addressing the principle of replacement, reduction and refinement of animal experiments (3Rs), human in vitro bone remodeling models are being developed. Despite increasing safety-, scientific-, and ethical concerns, fetal bovine serum (FBS), a nutritional medium supplement, is still routinely used in these models. To comply with the 3Rs and to improve the reproducibility of such in vitro models, xenogeneic-free medium supplements should be investigated. Human platelet lysate (hPL) might be a good alternative as it has been shown to accelerate osteogenic differentiation of mesenchymal stromal cells (MSCs) and improve subsequent mineralization. However, for a human in vitro bone model, hPL should also be able to adequately support osteoclastic differentiation and subsequent bone resorption. In addition, optimizing co-culture medium conditions in mono-cultures might lead to unequal stimulation of co-cultured cells. Here, we compared supplementation with 10% FBS vs. 10%, 5%, and 2.5% hPL for osteoclast formation and resorption by human monocytes (MCs) in mono-culture and in co-culture with (osteogenically stimulated) human MSCs. Our results indicate that the supplementation of hPL can lead to a less donor-dependent and more homogeneous osteoclastic differentiation of MCs when compared to supplementation with 10% FBS. In co-cultures, osteoclastic differentiation and resorption in the 10% FBS group was almost completely inhibited by MSCs, while the supplementation with hPL still allowed for resorption, mostly at low concentrations. The addition of hPL to osteogenically stimulated MSC mono- and MC-MSC co-cultures resulted in osteogenic differentiation and bone-like matrix formation, mostly at high concentrations. Therefore, we conclude that hPL could support both osteoclastic differentiation of human MCs and osteogenic differentiation of human MSCs in mono- and in co-culture, and that this can be balanced by the hPL concentration. Thus, the use of hPL could limit the need for FBS, which is currently commonly accepted for in vitro bone remodeling models.


title: Temperature and resources interact to shape phytoplankton size-abundance relationships at a continental scale

abstract: Communities contain more individuals of small species and fewer individuals of large species. The observed -3/4 slope relating mean size and mean abundance across communities (the  cross-community scaling relationship or CCSR) is thought to arise from a 3/4-power scaling of metabolic rate with body size. Assuming that 3/4-power metabolic scaling is universal, as claimed by the metabolic theory of ecology (MTE), size-abundance relationships should also be invariant with a scaling exponent of -3/4 or nearly so, across environmental conditions. However, we find that the CCSR slope is actually -1 overall (perhaps due to isometric metabolic scaling), and varies substantially across temperature and nutrient gradients in 1048 freshwater lake phytoplankton communities in the USA. The size-abundance relationship is most shallow at low temperatures and high nutrients, and steeper and relatively insensitive to nutrients at high temperatures. Phytoplankton communities have orders of magnitude more small or large cells depending on environmental conditions than would be predicted from the MTE. Although based on observational data, these results suggest that the environment alters either metabolic scaling or other poorly understood processes shaping community size distributions.

category: ecology


title: Haul-out behavior and aerial survey detectability of seals in the Bering and Chukchi seas

abstract: Ice-associated seals rely on sea ice for a variety of activities, including breeding, molting, pupping, and resting. In the Arctic, many of these activities occur in spring (April - June) as sea ice begins to melt and retreat northward. Rapid acceleration of climate change in Arctic ecosystems is therefore of concern as the quantity and quality of suitable habitat is forecast to decrease. In this paper, we use data collected from satellite-linked bio-loggers deployed between 2005 and 2020 to investigate the seasonal timing and environmental factors affecting haul-out behavior by ice-associated seals. We specifically focused on bearded (Erignathus barbatus), ribbon (Histriophoca fasciata), and spotted seals (Phoca largha) in the Bering and Chukchi seas. Because ringed seals (Phoca hispida) are unique in their use of snow lairs, they were not included and a separate analysis is warranted. In addition to providing baseline data on phenology, these data also allow us to quantify  availability, which is needed to accurately estimate abundance from aerial survey counts of these seals basking on ice (i.e., to correct for the proportion of animals that are in the water while surveys are conducted). Using generalized linear mixed pseudo-models to properly account for temporal autocorrelation, we fit models with covariates of interest (e.g., day-of-year, solar hour, age-sex class, wind speed, barometric pressure, temperature, precipitation) to examine their ability to explain variation in hourly haul-out probability. We found evidence for strong diurnal and within-season patterns in haul-out behavior, as well as strong weather effects (particularly wind and temperature). In general, seals were more likely to haul out on ice in the middle of the day and when wind speed was low and temperatures were higher. Haul-out probability increased through March and April, peaking in May and early June before declining again. The timing and frequency of haul-out events also varied based on species and age-sex class. For ribbon and spotted seals, models with year effects were highly supported, indicating that the timing and magnitude of haul-out behavior varied among years. However, we did not find evidence that haul-out timing was linked to annual sea ice extent. Our analysis emphasizes the importance of accounting for seasonal and temporal variation in haul-out behavior, as well as associated environmental covariates, when interpreting the number of seals counted in aerial surveys.


title: DecentTree: Scalable Neighbour-Joining for the Genomic Era

abstract:
SummaryNeighbour-Joining is one of the most widely used distance-based phylogenetic inference methods. However, current implementations do not scale well for datasets with more than 10,000 sequences. Given the increasing pace of generating new sequence data, particularly in outbreaks of emerging diseases, and the already enormous existing databases of sequence data for which NJ is a useful approach, new implementations of existing methods are warranted.

Here we present DecentTree, which provides highly optimised and parallel implementations of Neighbour-Joining and several of its variants. DecentTree is designed as a stand-alone application and a header-only library easily integrated with other phylogenetic software (e.g. it is integral in the popular IQ-TREE software). We show that DecentTree shows similar or improved performance over existing software (BIONJ, Quicktree, FastME, and RapidNJ), especially for handling very large alignments. For example, DecentTree is up to 6-fold faster than the fastest existing Neighbour-Joining software (e.g. RapidNJ) when generating a tree of 64,000 SARS-CoV-2 genomes.

Availability and implementationDecentTree is open source and freely available at https://github.com/iqtree/decenttree.

ContactMinh Bui: m.bui@anu.edu.au; Robert Lanfear: rob.lanfear@anu.edu.au

Supplementary informationSupplementary data are available at Bioinformatics online.

category: evolutionary biology


title: How connected are different multitrait phenotypes in a model diatom genus?

abstract: Marine diatoms are important primary producers that can undergo multitrait changes in response to environmental or demographic perturbations. Here, we investigated how flexible multitrait correlations are over hundreds of generations, and how lineage diversity and phenotype diversity are related. We used a perturbation-evolution experiment with Thalassiosira diatoms in which they were "knocked-off" their ancestral multitrait phenotype peak using repeated population bottlenecks, and were then allowed to grow unhindered as large populations. We found that most multitrait phenotypes were isolated but that in 10% of cases, phenotypes were connected by viable trajectories. Following the bottleneck perturbation, evolving in a +4{degrees}C environment favoured the discovery of novel multitrait phenotypes, while evolving in the ancestral environment most often resulted in the ancestral phenotype re-evolving. Finally, both trait values and trait correlations evolved in this experiment, with the most drastic changes in trait correlations being associated with lower growth rates. Our findings demonstrate that demographic events that result in decreases in fitness, such as population bottlenecks, have the potential to play an important role in the realised connectivity of phenotypes, as well as in shaping the relationship between lineage and phenotypic diversity in diatoms.


title: Salt stress alters the spectrum of de novo mutation available to selection during experimental adaptation of Chlamydomonas reinhardtii

abstract: The genetic basis of adaptation is driven not only by selection, but also by the spectrum of available mutations. Given that the rate of mutation is not uniformly distributed across the genome and varies depending on the environment, understanding the signatures of selection across the genome is aided by first establishing what the expectations of genetic change are from mutation. To determine the interaction between salt stress, selection, and mutation across the genome, we compared the rates and patterns of mutation observed in a selection experiment for salt tolerance in Chlamydomonas reinhardtii to those observed in mutation accumulation experiments with and without salt exposure. We found that salt stress led to an increased rate of indel mutations, but that many of these mutations were removed under selection. Finally, lines adapted to salt also showed excess clustering of mutations in the genome and the co-expression network, suggesting a role for positive selection in retaining mutations in particular compartments of the genome during the evolution of salt tolerance. Our study shows that characterizing mutation rates and spectra expected under stress helps disentangle the effects of environment and selection during adaptation.


title: Natural and human-mediated drivers of microevolution in Neotropical palms: a historical genomics approach

abstract:
O_LIMicroevolution in Amazonia has been far less documented than in temperate regions and still constitutes a major knowledge gap. Moreover, the actual influence of pre-Columbian societies through the Holocene remains unclear, although it could provide interesting insights on the relationship between natural and human-mediated evolutionary processes in driving microevolution.
C_LIO_LIBecause they are widespread and traditionally managed since pre-Columbian times, Neotropical palms are choice models to investigate the drivers of microevolution in Amazonia. In this study, we carried out a preliminary exploration of the genomic diversity in two pairs of congeneric palm species in French Guiana (Astrocaryum spp. and Oenocarpus spp.).
C_LIO_LIWe built upon an original sampling design, taking into account both regional climate variations and local-scale pre-Columbian occupation, and designed a new target capture kit of 20,000 molecular probes scattered across exonic regions of more than 5,000 nuclear genes in Arecoideae ("ARECO5000+"). Hundreds of palm libraries were sequenced through Illumina sequencing, providing a unique - high-coverage - genomic dataset in these non-model species.
C_LIO_LIWe explored patterns of genomic diversity and differentiation within and across populations, bringing state-of-the-art knowledge about the roles of climate adaptation and pre-Columbian domestication. By documenting original cases of "incipient" domestication, these pioneer results open new avenues toward a better understanding of microevolution in Amazonia and of the impact of pre-Columbian societies on present-day biodiversity patterns.
C_LI


title: Social determinants of health and disease in companion dogs: A cohort study from the Dog Aging Project

abstract: Exposure to social environmental adversity is associated with health and survival in many social species, including humans. However, little is known about if and how these health and mortality effects vary across the lifespan, largely due to the difficulty of studying long-lived organisms across much of their lifespan. Here, we leveraged a relatively new and powerful model for human aging, the companion dog, to investigate which components of the social environment are associated with dog health and how these associations vary across the lifespan. We drew on comprehensive survey data collected on 21,410 dogs from the Dog Aging Project and identified five factors that together explained 33.7% of the variation in a dogs social environment. Factors capturing financial and household adversity were associated with poorer health and lower physical mobility in companion dogs, while factors that captured social support, such as living with other dogs, were associated with better health when controlling for dog age and weight. Some of these associations differed across a dogs lifespan, including a stronger relationship between owner age and health in younger (as compared to older) dogs. Taken together, these findings suggest the importance of income, stability, and owner age on owner-reported health outcomes in companion dogs and point to potential behavioral and/or environmental modifiers that can be used to promote healthy aging across species.


title: TwinEQTL: Ultra Fast and Powerful Association Analysis for eQTL and GWAS in Twin Studies

abstract: We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model (LMM) for twin genome-wide association study (GWAS) data. Instead of analyzing all twin samples together with LMM, TwinEQTL first splits twin samples into two independent groups on which multiple linear regression analysis can be validly performed separately, followed by an appropriate meta-analysis-like approach to combine the two non-independent test results. Through mathematical derivations, we prove the validity of TwinEQTL algorithm and show that the correlation between two dependent test statistics at each single-nucleotide polymorphism (SNP) are independent of its minor allele frequency (MAF). Thus the correlation is constant across all SNPs. Through simulations, we show empirically that TwinEQTL has well controlled type I error with negligible power loss compared to the gold-standard linear mixed effects models. To accommodate eQTL analysis with twin subjects, we further implement TwinEQTL into a R package with much improved computational efficiency. Our approaches provide a significant leap in terms of computing speed for GWAS and eQTL analysis with twin samples.

category: genetics


title: High-throughput Oligopaint screen identifies druggable regulators of genome folding

abstract: Although the molecular rules governing genome organization are being quickly elucidated, relatively few proteins regulating this process have been identified. To address this gap, we developed a fully automated imaging pipeline, called HiDRO (high-throughput DNA or RNA labeling with optimized Oligopaints), that permits quantitative measurement of chromatin interactions across a large number of samples. Using HiDRO, we screened the human druggable genome and identified >300 factors that regulate chromatin folding during interphase, including 43 validated hits that either increase or decrease interactions between topological associating domains (TADs). We discovered that genetic or chemical inhibition of the ubiquitous kinase GSK3A enhances long-range interactions by dysregulating cohesin-mediated chromatin looping. Collectively, these results highlight a noncanonical role for GSK3A signaling in nuclear architecture and underscore the broader utility of HiDRO-based screening to identify novel mechanisms that drive the spatial organization of the genome.


title: Statistical learning for sparser fine-mapped polygenic models: the prediction of LDL-cholesterol

abstract: Polygenic risk scores quantify the individual genetic predisposition regarding a particular trait. We propose and illustrate the application of existing statistical learning methods to derive sparser models for genome-wide data with a polygenic signal. Our approach is based on three consecutive steps. First, potentially informative loci are identified by a marginal screening approach. Then, fine-mapping is independently applied for blocks of variants in linkage disequilibrium, where informative variants are retrieved by using variable selection methods including boosting with probing and stochastic searches with the Adaptive Subspace method. Finally, joint prediction models with the selected variants are derived using statistical boosting. In contrast to alternative approaches relying on univariate summary statistics from genome-wide association studies, our three-step approach enables to select and fit multivariable regression models on large-scale genotype data. Based on UK Biobank data, we develop prediction models for LDL-cholesterol as a continuous trait. Additionally, we consider a recent scalable algorithm for the Lasso. Results show that statistical learning approaches based on fine-mapping of genetic signals result in a competitive prediction performance compared to classical polygenic risk approaches, while yielding sparser risk models that tend to be more robust regarding deviations from the target population.


title: Uncovering the roles of lignin-related genes in disease resistance in maize using mutant and association analysis

abstract:
Brown midrib (BMR) maize harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate NY highlighted the disease susceptibility of commercially grown BMR maize hybrids. We found the bm1, bm2, bm3 and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot, and anthracnose leaf blight) and bacterial (Stewarts wilt) diseases. The bm1, bm2 and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot, and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot. Co-localization of quantitative trait loci and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high-resolution, genome-wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered SNP associations for resistance to NLB, but did not implicate natural functional variation at bm1-bm5. Strong associations implicated a suite of diverse candidate genes, including lignin-related genes such as a {beta}-glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP-like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and non-silage purposes.

Core IdeasO_LIBrown midrib mutants (bm1-bm4) in maize, characterized as mutations with reduced lignin content, are susceptible to a range of foliar pathogens.
C_LIO_LISeveral brown midrib mutants in maize show enhanced susceptibility to stalk rot and ear rot pathogens.
C_LIO_LIGenome wide association analysis identified a number of diverse candidate genes associated with resistance to northern leaf blight in maize, including lignin-related genes involved in the monolignol pathway, developmental genes and transcription factors.
C_LIO_LIAssociation analysis for resistance to NLB implicated a {beta}-glucosidase gene cluster, including Zmbglu24 and Zmbglu25 known for targeting monolignols and contributing to [~]15% phenotypic variation.
C_LIO_LIhct11, which plays an important role in the monolignol pathway, was implicated for resistance to northern leaf blight in maize with potential for multiple stress tolerance.
C_LI


title: Population genomics unravels the Holocene history of Triticum-Aegilops species

abstract: Deep knowledge of crop biodiversity is essential to improve global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its wild relatives (a.k.a. wheats) remains elusive. By analyzing whole-genome sequences of 795 wheats, we found that bread wheat originated southwest of the Caspian Sea [~]11,700 years ago and underwent a slow speciation process, lasting [~]3,300 years due to persistent gene flow from wild relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia, and East Asia [~]7,000 to [~]5,000 years ago, shaping a diversified but occasionally convergent adaptive landscape of bread wheat in novel environments. Opposite to cultivated wheat, wild wheat populations have declined by [~]82% in the past [~]2,000 years due to the food choice shift of humans, and likely continue to drop because of the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to improve global food security.


title: Capped nascent RNA sequencing reveals novel therapy-responsive enhancers in prostate cancer

abstract: Mounting evidence suggests that enhancer RNA (eRNA) transcription start sites (TSSs) provide higher sensitivity and specificity for enhancer identification than histone modifications and chromatin accessibility. The extent to which changes in eRNA transcription correspond to changes in enhancer activity, however, remains unclear. Here, we used precision run-on and capped RNA sequencing (PRO-cap) to assess changes in enhancer activity in response to treatment with the androgen receptor signaling inhibitor, enzalutamide (ENZ). We identified 6,189 high-confidence candidate enhancers in the human prostate cancer cell line, LNCaP; 853 of which demonstrated significant changes in activity in response to drug treatment. Notably, we found that 67% and 54% of drug-responsive enhancers did not show similar changes in activity in previous studies that utilized ChIP-seq and ATAC-seq, respectively. Strikingly, 79% of regions with increased eRNA transcription showed no other biochemical alterations, implying that PRO-cap can capture a set of precise changes in enhancer activity that classical approaches lack the sensitivity to detect. We performed in vivo functional validations of candidate enhancers and found that CRISPRi targeting of PRO-cap-specific drug-responsive enhancers impaired ENZ regulation of downstream target genes, suggesting that changes in eRNA TSSs mark true biological changes in enhancer activity with high sensitivity. Our study highlights the utility of using PRO-cap as a complementary approach to canonical biochemical methods for detecting precise changes in enhancer activity and, in particular, for better understanding disease progression and responses to treatment.

category: genomics


title: High quality genomes corroborate 29 chromosomes of the haploid Hyles (Lepidoptera: Sphingidae) karyotype

abstract:
FISH analysis of the karyotype revealed n = 29 chromosomes in Hyles euphorbiae. The measured genome sizes of H. euphorbiae and H. vespertilio are estimated to have average 1C DNA values of 472 and 562 Mb respectively. The H. euphorbiae genome was PacBio sequenced and amended by Hi-C Illumina data yielding a 504 Mb assembly with a scaffold N50 of 18.2 Mb and 99.9% of the data being represented by the 29 largest scaffolds, corroborating the haploid karyotype. Chromosome length estimations based on karyotype image data provide an additional quality metric of the assembled chromosome sizes. Hi-C data was also used for chromosome-level scaffolding of the published H. vespertilio genome, leading to a second assembly (651 Mb) with scaffold N50 of 22 Mb, 98% in the 29 largest scaffolds representing the chromosomes. The larger H. vespertilio genome size was accompanied by a proportional increase of repeats from 45% in H. euphorbiae to nearly 55% in H. vespertilio.

In both Hyles species, the three wing pattern genes, optix, wingless/wint-1 and cortex, were found on chromosomes 23, 4 and 17, respectively. Peaks of divergence surrounding wingless/wnt-1 and cortex provide candidate genomic areas in which wing patterns are determined in this genus.


title: A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomics.

abstract: Direkli Cave, located in the Taurus Mountains of southern Turkey, was occupied by Late Epipaleolithic hunters-gatherers for the seasonal hunting and processing of game including large numbers of wild goats. We report genomic data from new and published Capra specimens from Direkli Cave and, supplemented with historic genomes from multiple Capra species, find a novel lineage best represented by a ~14,000 year old 2.59X genome sequenced from specimen Direkli4. This newly discovered Capra lineage is a sister clade to the Caucasian tur species (Capra cylindricornis and Capra caucasica), both now limited to the Caucasus region. West Eurasian domestic goats in the past, but not those today, appear enriched for Direkli4-specific alleles, and we further identify genomic regions introgressed in domestic goats with high affinity to Direkli4. This forgotten "Taurasian tur" likely survived Late Pleistocene climatic change in a Taurus Mountain refugia and its genomic fate is unknown.


title: Life-long Dietary Restrictions have Negligible or Damaging Effects on Late-life Cognitive Performance: A Key Role for Genetics in Outcomes

abstract: Several studies report that caloric restriction (CR) or intermittent fasting (IF) can improve cognition, while others report limited or no cognitive benefits. Here, we compare the effects of 20% CR, 40% CR, 1-day IF, and 2-day IF feeding paradigms to ad libitum controls (AL) on Y-maze working memory and contextual fear memory (CFM) in a large population of Diversity Outbred mice that model the genetic diversity of humans. While CR and IF interventions improve lifespan, we observed no enhancement of working memory or CFM in mice on these feeding paradigms, and report 40% CR to be damaging in the context of long-term memory. Using Quantitative Trait Loci mapping, we identified the gene Slc16a7 to be associated with late-life long-term memory outcomes in mice on lifespan promoting feeding paradigms. Limited utility of dieting and fasting on memory in mice that recapitulate genetic diversity in the human population highlights the need for anti-aging therapeutics that promote cognitive function, with a neuronal monocarboxylate transporter encoded by Slc16a7 highlighted as novel target.

category: animal behavior and cognition


title: Production of adaptive movement patterns via an insect inspired Spiking Neural Network Central Pattern Generator.

abstract: Navigation in ever-changing environments requires effective motor behaviours. Many insects have developed adaptive movement patterns which increase their success in achieving navigational goals. A conserved brain area in the insect brain, the Lateral Accessory Lobe, is involved in generating small scale search movements which increase the efficacy of sensory sampling. When the reliability of an essential navigational stimulus is low, searching movements are initiated whereas if the stimulus reliability is high, a targeted steering response is elicited. Thus the network mediates an adaptive switching between motor patterns. We developed Spiking Neural Network models to explore how an insect inspired architecture could generate adaptive movements in relation to changing sensory inputs. The models are able to generate a variety of adaptive movement patterns, the majority of which are of the zig-zagging kind, as seen in a variety of insects. Furthermore, these networks are robust to noise. Because a large spread of network parameters lead to the zig-zagging movement dynamics, we conclude that the investigated network architecture is inherently well suited to generating adaptive movement patterns.


title: Design of a Minimal di-Nickel Hydrogenase Peptide

abstract:
The most ancient processes for energy production in the evolution of life involve the reversible oxidation of molecular hydrogen by hydrogenase. Extant hydrogenase enzymes are complex, comprising hundreds of amino acids and multiple cofactors. We designed a 13 amino acid nickel-binding peptide capable of robustly producing molecular hydrogen from protons under a wide variety of conditions. The peptide forms a di-nickel cluster structurally analogous to a Ni-Fe cluster in [NiFe]-hydrogenase and the Ni-Ni cluster in acetyl-CoA synthase (ACS), two ancient, extant proteins central to metabolism. These experimental results clearly demonstrate that modern enzymes, despite their enormous complexity, likely evolved from simple peptide precursors on early Earth.

One Sentence SummarySmall metal-binding peptides were the likely precursors of modern enzymes.

category: biochemistry


title: Simulating the Tumor Microenvironment for Immune Cell Interactions via Deployable Extrusion Bioprinting

abstract: Three-dimensional (3D) bioprinting has emerged as a promising tool for constructing tumor microenvironments (TME) for cancer modelling in vitro. Realizing the translational impacts of 3D bioprinting for cancer research necessitates innovation in bioprinting workflows which integrate affordability, user-friendliness, and biological relevance. Herein, we demonstrate  bioArm, a simple, yet highly effective extrusion bioprinting platform, which can be folded into a carry-on pack, and rapidly deployed between bio-facilities. BioArm enabled TME reconstruction in the form of 3D core-shell tumoroids with cancer-associated fibroblasts (CAFs). Tumoroids showed the presence of a heterogenous population of CAFs with de novo synthesized extracellular matrices, demonstrating more in vivo-like characteristics compared to conventional 2D co-culture models. Embedding the 3D printed tumoroids in an immune cell laden collagen matrix permitted tracking of the interaction between immune cells and tumoroids, and subsequent immunotherapy treatments. Our deployable extrusion bioprinting workflow could significantly widen the accessibility of 3D bioprinting for gaining mechanistic understanding in TME, and for developing strategies in cancer drug testing.

category: bioengineering


title: Data Driven Control of Vagus Nerve Stimulation for the Cardiac System

abstract: 1Vagus nerve stimulation is an emerging therapy that seeks to offset pathological conditions by electrically stimulating the vagus nerve through cuff electrodes, where an electrical pulse is defined by several parameters such as pulse amplitude, pulse width, and pulse frequency. This electroceutical therapy has been approved for epilepsy, and treatment resistant depression. Currently, vagus nerve stimulation is under investigation for the treatment of heart failure, heart arrhythmia, hypertension, and gastric motility disorders. Through several clinical trials that sought to assess vagus nerve stimulation for the treatment of heart failure, stimulation parameters were determined heuristically and the results were left inconclusive, which has led to the suggestion of using a closed-loop approach to optimize the stimulation parameters. A recent investigation has demonstrated highly specific control of cardiac physiology by selectively activating different fibers in the vagus nerve. When multiple locations and multiple stimulation parameters are considered for optimization, the design of closed-loop control becomes considerably more challenging. To address this challenge, we investigated a data-driven control scheme for both modeling and controlling the rat cardiac system. Using an existing in silico physiological model of a rat heart to generate synthetic input-output data, we trained a long short-term memory network (LSTM) to map the effect of stimulation on the heart rate and the blood pressure. The trained LSTM was utilized in a model predictive control framework to optimize the vagus nerve stimulation parameters for set point tracking of the heart rate and the blood pressure in closed-loop simulations. Additionally, we altered the underlying in silico physiological model to consider intra-patient variability, and diseased dynamics from increased sympathetic tone in designing closed-loop VNS strategies. Throughout the different simulation scenarios, we leveraged the design of the controller to demonstrate alternative clinical objectives. Our results show the controller can optimize stimulation parameters to achieve set-point tracking with nominal offset while remaining computationally efficient. Furthermore, we show a controller formulation that compensates for mismatch due to intra-patient variabilty, and diseased dynamics. This study demonstrates the first application and a proof-of-concept for using a purely data-driven approach for the optimization of vagus nerve stimulation parameters in closed-loop control of the cardiac system.


title: Functional feature selection reveals the inner cell mass in human pre-implantation embryo single cell RNA sequencing data

abstract: A major challenge with single cell gene expression data is to discern meaningful cellular heterogeneity from technical or biological noise. To address this challenge, we present Entropy Sorting, a mathematical framework that distinguishes genes indicative of cell identity. On synthetic data we demonstrate the removal of noisy signals to reveal a higher resolution of gene expression patterns than commonly used feature selection methods. We then apply Entropy Sorting to human pre-implantation embryo scRNA-seq data. Previous studies failed to identify a distinct signature of the inner cell mass (ICM), suggesting that lineage segregation in the human embryo does not follow the paradigm established in mouse. However, Entropy Sorting identifies a set of highly informative genes that clearly separate the ICM, Trophectoderm, Epiblast and Hypoblast and reveals sequential lineage bifurcations as in mouse. Entropy sorting thus provides a powerful approach for maximising information extraction from high dimensional datasets such as scRNA-seq data.


title: Recovery of 447 Eukaryotic bins reveals major challenges for Eukaryote genome reconstruction from metagenomes.

abstract: An estimated 8.7 million eukaryotic species exist on our planet. However, recent tools for taxonomic classification of eukaryotes only dispose of 734 reference genomes. As most Eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recover Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of Eukaryotic genomes from metagenomes. This study assessed the reconstruction of Eukaryotic genomes using 215 metagenomes from diverse environments using the EukRep pipeline. We obtained 447 eukaryotic bins from 15 classes (e.g., Saccharomycetes, Sordariomycetes, and Mamiellophyceae) and 16 orders (e.g., Mamiellales, Saccharomycetales, and Hypocreales). More than 73% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic and anthropogenic terrestrial. However, only 93 bins showed taxonomic classification to (9 unique) genera and 17 bins to (6 unique) species. A total of 193 bins contained completeness and contamination measures. Average completeness and contamination were 44.64% ({sigma}=27.41%) and 3.97% ({sigma}=6.53%), respectively. Micromonas commoda was the most frequent taxa found while Saccharomyces cerevisiae presented the highest completeness, possibly resulting from a more significant number of reference genomes. However, mapping eukaryotic bins to the chromosomes of the reference genomes suggests that completeness measures should consider both single-copy genes and chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, intron removal after assembly, and improved reference genomes databases.


title: MOCCS profile analysis clarifies the cell type dependency of transcription factor-binding sequences and cis-regulatory SNPs in humans

abstract:
BackgroundTranscription factors (TFs) bind to DNA by recognizing sequences specific to each TF. ChIP-seq provides DNA sequences from in vivo TF-binding sites in a genome-wide manner. De novo motif discovery usually provides multiple motifs, even from a single ChIP-seq sample, reflecting heterogeneous sequence contexts. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the in vivo diversity of TF-binding DNA sequences across different TFs and cell types remains largely unexplored.

ResultsHere, we systematically analyzed the DNA-binding sequences of human TFs by applying MOCCS2, our k-mer-based motif discovery method, to a compendium of ChIP-seq samples across diverse TFs and cell types. We represent ChIP-seq samples as profiles of the binding specificity scores (MOCCS2scores) for each k-mer, which we call MOCCS profiles. Using the MOCCS profiles, we compared TF-binding sequences among ChIP-seq samples across different TFs and cell types and found that one-third of the analyzed TFs exhibited cell type dependency in MOCCS profiles. Moreover, the differences in MOCCS2scores ({Delta}MOCCS2scores) were able to predict the effect of variants on TF binding, in line with the results of in vitro and in vivo assays. We also demonstrate the use of the {Delta}MOCCS2score to interpret non-coding GWAS-SNPs as TF-affecting SNPs and associate them with candidate responsible TFs and cell types.

ConclusionsWe revealed the cell type dependency of in vivo TF-binding sequences in humans and demonstrated that {Delta}MOCCS2scores can help to interpret GWAS-SNPs. Our study would provide the basis for the investigation of gene expression regulation and non-coding disease-associated variants in humans.


title: Multi-Head Attention-based U-Nets for Predicting Protein Domain Boundaries Using 1D Sequence Features and 2D Distance Maps

abstract: The information about the domain architecture of proteins is useful for studying protein structure and function. However, accurate prediction of protein domain boundaries (i.e., sequence regions separating two domains) from sequence remains a significant challenge. In this work, we develop a deep learning method based on multi-head U-Nets (called DistDom) to predict protein domain boundaries utilizing 1D sequence features and predicted 2D inter-residue distance map as input. The 1D features contain the evolutionary and physicochemical information of protein sequences, whereas the 2D distance map includes the structural information of proteins that was rarely used in domain boundary prediction before. The 1D and 2D features are processed by the 1D and 2D U-Nets respectively to generate hidden features. The hidden features are then used by the multi-head attention to predict the probability of each residue of a protein being in a domain boundary, leveraging both local and global information in the features. The residue-level domain boundary predictions can be used to classify proteins as single-domain or multi-domain proteins. It classifies the CASP14 single-domain and multi-domain targets at the accuracy of 72.7%, 8.02% more accurate than the state-of-the-art method. Tested on the CASP14 multi-domain protein targets with expert annotated domain boundaries, the average per-target F1 measure score of the domain boundary prediction by DistDom is 0.241, 18.72% higher than the state-of-the-art method.


title: NEUROeSTIMator: Using Deep Learning to Quantify Neuronal Activation from Single-Cell and Spatial Transcriptomic Data

abstract: Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates signals of activation distributed throughout the broader transcriptome to estimate neuronal activation in a way that is robust against differences in species, cell type, and brain region. We demonstrate this methods ability to accurately detect neuronal activity in previously published single cell and time course studies of activity-induced gene expression. Further, using spatial transcriptomic techniques, we demonstrate the models ability to identify patterns of learning-induced activation. In conclusion, NEUROeSTIMator is a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.


title: Subtractive proteomics analysis to uncover the potent drug targets for distinctive drug design of Candida auris

abstract:
Candida auris is a serious health concern of current world that possess serious global health threat and is emerging at a high rate. Available antifungal drugs are failing to combat this pathogen as they are growing resistance toward those drugs and some strains have already showed resistant to all three available antifungal drugs in the market. Finding alternative treatments is a must, therefore, to save lives from this foe. To make the way easier for developing new treatments, we have made some insilico analysis of this pathogen to identify suitable targets for designing drugs and also suggested some potential metabolites to test in vivo condition after some computational analysis. After the subtraction of duplicate, non-essential, human homologs, non-metabolic, human microbiome similar and druggable proteins we ended up with three proteins (XP_028890156.1, XP_028891672.1 and XP_028891858.1) from a total of 5441 C. auris proteins. Blocking those proteins will result in the destruction of the pathogen while the host will remain safe from unintentional blocking. Their subcellular locations and interaction with high number of proteins also indicate their suitability as drug target candidates. After analyzing in silico docking of 29 potential antifungal from plant origin with those three proteins we selected Caledonixanthone E, Viniferin, Glaucine, Jatrorrhizine as the most potent weapon to block those proteins as they showed higher binding affinity. Furthermore, they were predicted to be safe and also showed proper ADME properties (Figure 1).

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title: Kinome Inhibition States and Multiomics Data Enable Prediction of Cell Viability in Diverse Cancer Types

abstract: Protein kinases play a vital role in a wide range of cellular processes and compounds that inhibit kinase activity have emerged as a primary focus for targeted therapy development in cancer. This has inspired work that characterizes the spectrum of kinases targeted by specific inhibitors and the inclusion of these inhibitors in large-scale cell viability screening efforts. Previous work with smaller datasets have used baseline profiling of cell lines and limited kinome profiling data to attempt to predict small molecule effects on cell viability, but these efforts did not use multi-dose kinase profiles and achieved low accuracy with very limited external validation. This work focuses on two primary data types, kinase inhibitor profiles and gene expression, to predict the results of cell viability screening. We describe the process by which we combined these data sets, examined their properties in relation to cell viability and finally developed a set of computational models that achieve reasonable prediction accuracy (R2 of 0.78 and RMSE of 0.154). Using these models, we identified a set of kinases, several of which are understudied, that are strongly influential in the cell viability prediction models. In addition, we also tested to see if a wider range of multiomics data sets could improve the model results. Finally, we validated a small subset of the model predictions in several triple-negative and HER2 positive breast cancer cell lines demonstrating that the model performs well with compounds and cell lines that were not included in the training data set. Overall, this result demonstrates that generic knowledge of the kinome is predictive of very specific cell phenotypes, and has the potential to be integrated into targeted therapy development pipelines.


title: SIQ: easy quantitative measurement of mutation profiles in sequencing data

abstract: Establishing mutational outcomes after genome editing is of increasing importance with the advent of highly efficient genome-targeting tools. Next-generation sequencing (NGS) has become a vital method to investigate the extent of mutagenesis at specific target sites. Thus, robust and simple-to-use software that enables researchers to retrieve mutation profiles from NGS data is needed. Here, we present Sequence Interrogation and Quantification (SIQ), a tool that can analyse sequence data of any targeted experiment (e.g. CRISPR, I-SceI, TALENs) with a focus on event classification such as deletions, single-nucleotide variations, (templated) insertions and tandem duplications. SIQ results can be directly analysed and visualized via SIQPlotteR, an interactive web tool that we made freely available. Using novel and insightful tornado plot visualizations as outputs we illustrate that SIQ readily identifies differences in mutational signatures obtained from various DNA-repair deficient genetic backgrounds. SIQ greatly facilitates the interpretation of complex sequence data by establishing mutational profiles at specific loci and is, to our knowledge, the first tool that can analyse Sanger sequence data as well as short and long-read NGS data (e.g. Illumina and PacBio).


title: Quantum chemical elucidation of a sevenfold symmetric bacterial antenna complex

abstract: The light-harvesting complex 2 (LH2) of purple bacteria is one of the most studied photosynthetic antenna complexes. Its symmetric structure and ring-like bacteriochlorophyll arrangement make it an ideal system for theoreticians and spectroscopists. LH2 complexes from most bacterial species are thought to have eightfold or ninefold symmetry, but recently a sevenfold symmetric LH2 structure from the bacterium Mch. purpuratum was solved by Cryo-Electron microscopy. This LH2 also possesses unique nearinfrared absorption and circular dichroism (CD) spectral properties. Here we use an atomistic strategy to elucidate the spectral properties of Mch. purpuratum LH2 and understand the differences with the most commonly studied LH2 from Rbl. acidophilus. Our strategy exploits a combination of molecular dynamics simulations, multiscale polarizable quantum mechanics/molecular mechanics calculations, and lineshape simulations. Our calculations reveal that the spectral properties of LH2 complexes are tuned by site energies and exciton couplings, which in turn depend on the structural fluctuations of the bacteriochlorophylls. Our strategy proves effective in reproducing the absorption and CD spectra of the two LH2 complexes, and in uncovering the origin of their differences. This work proves that it is possible to obtain insight into the spectral tuning strategies of purple bacteria by quantitatively simulating the spectral properties of their antenna complexes.


title: Structure and ensemble refinement against SAXS data: combining MD simulations with Bayesian inference or with the maximum entropy principle

abstract: Small-angle X-ray scattering (SAXS) is a powerful method for tracking conformational transitions of proteins or soft-matter complexes in solution. However, the interpretation of the experimental data is challenged by the low spatial resolution and the low information content of the data, which lead to a high risk of overinterpreting the data. Here, we illustrate how SAXS data can be integrated into all-atom molecular dynamics (MD) simulation to derive atomic structures or heterogeneous ensembles that are compatible with the data. Besides providing atomistic insight, the MD simulation adds physico-chemical information, as encoded in the MD force fields, which greatly reduces the risk of overinterpretation. We present an introduction into the theory of SAXS-driven MD simulations as implemented in GROMACS-SWAXS, a modified version of the GROMACS simulation software. We discuss SAXS-driven parallel-replica ensemble refinement with commitment to the maximum entropy principle as well as a Bayesian formulation of SAXS-driven structure refinement. Practical considerations for running and interpreting the simulations are presented. The methods are freely available via GitLab at https://gitlab.com/cbjh/gromacs-swaxs.


title: Experimental evolution in TP53 deficient gastric organoids recapitulates tumorigenesis

abstract:
The earliest events during human tumor initiation are poorly characterized but may hold clues as to how to detect and prevent malignancy. Here we model occult pre-neoplasia by engineering TP53 deficiency, a common and early event in gastric cancer, into human gastric organoids. By performing experimental evolution in multiple clonally derived cultures over two years we define causal relationships between this common initiating genetic lesion and resulting phenotypes. TP53 loss elicited progressive aneuploidy, including copy number alterations and complex structural variants that are common in gastric cancers and which follow preferred temporal orders. Longitudinal single cell sequencing of TP53 deficient gastric organoids similarly indicates progression towards malignant transcriptional programs. Moreover, lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programs repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a striking degree of phenotypic convergence in pre-malignant epithelial organoids, implying that the earliest stages of tumorigenesis may be predictable while illuminating evolutionary constraints and barriers to malignant transformation.

Graphical abstract

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category: cancer biology


title: Experimental evolution in TP53 deficient human gastric organoids recapitulates tumorigenesis