Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior Representational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational (dis-)similarity matrices (RDM or RSM), which characterize the pairwise (dis-)similarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This  equal weights assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, in case of model comparison, may lead them to select an inferior model. The aim of this work is twofold: First, we sought to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RSM correspondence and affects model selection. Previous work suggested that reweighting can improve model selection in RSA but it has remained unclear to what extent these results generalize across datasets and data modalities. To draw more general conclusions, we utilized a range of publicly available datasets and three popular deep neural networks (DNNs). Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We found that reweighting individual model units markedly improved the fit between model RSMs and target RSMs derived from several fMRI and behavioral datasets and affected model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RSM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally show that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain, and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the correspondence between representational spaces.
Region-specific microRNA alterations in marmosets carrying SLC6A4 polymorphisms are associated to anxiety-like behavior. Psychiatric diseases such as depression and anxiety are multifactorial conditions, highly prevalent in western societies. Human studies have identified a number of high-risk genetic variants for these diseases. Among them, polymorphisms in the promoter region of the serotonin transporter gene (SLC6A4) have attracted much attention. However, due to the paucity of experimental models, molecular alterations induced by these genetic variants and how they correlate to behavioral deficits have not been examined. Marmosets have emerged as a powerful model in translational neuroscience to investigate molecular underpinnings of complex behaviors. Here, we took advantage of naturally occurring genetic polymorphisms in marmoset SLC6A4 gene that have been linked to anxiety-like behaviors. Using FACS-sorted cells from different brain regions, we revealed that marmosets bearing different SLC6A4 variants exhibit distinct microRNAs signatures in a region of the prefrontal cortex whose activity has been consistently altered in patients with depression/anxiety. We also identified DCC, a gene previously linked to these diseases, as a downstream target of the dysregulated microRNAs. Significantly, we showed that levels of both microRNAs and DCC in this region were highly correlated to anxiety-like behaviors as well as to the response to citalopram, a selective serotonin re-uptake inhibitor and widely prescribed anti-depressant. Our findings establish links between genetic variants, molecular modifications in specific cortical regions and complex behavioral/pharmacological responses, providing new insights into gene-behavior relationships underlying human psychopathology.
Parallel Characterization of cis-Regulatory Elements for Multiple Genes Using CRISPRpath Current pooled CRISPR screens for cis-regulatory elements (CREs) can only accommodate one gene based on its expression level. Here, we describe CRISPRpath, a scalable screening strategy for parallelly characterizing CREs of genes linked to the same biological pathway and converging phenotypes. We demonstrate the ability of CRISPRpath for simultaneously identifying functional enhancers of six genes in the 6-thioguanine-induced DNA mismatch repair pathway using both CRISPR interference (CRISPRi) and CRISPR nuclease (CRISPRn) approaches. 60% of the identified enhancers are known promoters with distinct epigenomic features compared to other active promoters, including increased chromatin accessibility and interactivity. Furthermore, by imposing different levels of selection pressure, CRISPRpath can distinguish enhancers exerting strong impact on gene expression from those exerting weak impact. Our results offer a nuanced view of cis-regulation and demonstrate that CRISPRpath can be leveraged for understanding the complex gene regulatory program beyond transcriptional output at scale. Task-independent metrics of computational hardness predict human cognitive performance The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of cognitive tasks using a set of task-independent metrics related to the computational resource requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that they predict both time spent on a task as well as accuracy in three canonical cognitive tasks. Our findings demonstrate that performance in cognitive tasks can be predicted based on generic metrics of their inherent computational hardness.

TeaserThe ability of humans to solve cognitive tasks is affected by generic mathematical properties of problems related to their computational complexity. Topology and adenocarcinoma cell localization dataset on the labyrinthin biomarker. The discovery and characterization of tumor associated antigens is increasingly important to advance the field of immuno-oncology. Data on the, 1) topology, 2) amino acid (a.a.) homology analyses and 3) cell surface localization are presented as evidence in support of labyrinthin as a pan-adenocarcinoma marker. Multiple bioinformatics tools were used to collectively predict calcium binding domain(s), N-myristoylation sites, kinase II phosphorylation sites, and transmembrane domain(s) with predicted N- and C-termini orientations. Sequence homology comparisons were found and alignments made for labyrinthin (255 a.a.) vs. the intracellular aspartyl/asparaginyl beta-hydroxylase (ASPH; 758 a.a.) and the ASPH-gene related protein junctate (299 a.a.), which are both type II proteins. The epitopes for commonly used MCA 44-3A6 anti-labyrinthin and FB-50 anti-ASPH/junctate antibodies were present in all three proteins. The selective expression of labyrinthin was investigated by third party fluorescent activated cell sorter (FACS) analyses of MCA 44-3A6 binding to non-permeabilized adenocarcinoma and normal cell line models. Labyrinthin was detected on non-permeabilized A549 human lung adenocarcinoma cells, but not on normal WI-38 human lung fibroblasts nor primary cultures of normal human glandular-related cells. Microscopic images of immunofluorescent labelled MCA 44-3A6 binding to A549 cells at random cell cycle stages complement the FACS results by further showing that labyrinthin persisted on the cell surfaces along with some cell internalization within 20 minutes. The dataset presented herein is related to research article: "Labyrinthin: A distinct pan-adenocarcinoma diagnostic and immunotherapeutic tumor specific antigen" by Babich et al., Heliyon, 2022 [1].

Specifications Table

O_TBL View this table:
org.highwire.dtl.DTLVardef@19222bborg.highwire.dtl.DTLVardef@1264bcdorg.highwire.dtl.DTLVardef@13a8158org.highwire.dtl.DTLVardef@1dcf0org.highwire.dtl.DTLVardef@503a9f_HPS_FORMAT_FIGEXP  M_TBL C_TBL Value of the data O_LIBecause identification and characterization of neoantigens [3, 4, 5] are rare yet increasingly important for diagnostics and therapeutics, the identification of labyrinthin as a pan-adenocarcinoma target is significant for further study by clinicians and cancer researchers.
C_LIO_LIThe data provide a basis to determine to what extent labyrinthin is a distinguishing marker for adenocarcinomas vs. conventional methods.
C_LIO_LIThe results indicate that therapeutic strategies can be employed that take advantage of labyrinthins convenient presence on adenocarcinoma cell surfaces.
C_LIO_LIThe discovery of a calcium binding sequence in labyrinthin provides a basis to research if it is key to explaining the long-known phenomena of elevated calcium and irregular signaling in cancer cells [8, 9].
C_LIO_LIThe data reveal a need to explore distinctions between ASPH and labyrinthin, in particular because ASPH [10, 11] and labyrinthin-based treatments have already been FDA approved for clinical trials.
C_LI Venomics and antivenomics of Indian spectacled cobra (Naja naja) from the Western Ghats Venom proteome profiling of Naja naja from the Western Ghats region in Kerala was achieved through SDS-PAGE and RP-HPLC followed by Q-TOF LC-MS/MS analysis, incorporating PEAKS and Novor assisted de novo sequencing methodologies. A total of 115 proteins distributed across 17 different enzymatic and non-enzymatic venom protein families were identified through conventional and 39 peptides through homology-driven proteomics approaches. Fourteen peptides derived through de novo complements the Mascot data indicating the importance of homology-driven approaches in improving protein sequence information. Among the protein families identified, glutathione peroxidase and endonuclease were reported for the first time in the Indian cobra venom. Immunological cross-reactivity assessed using Indian polyvalent antivenoms suggested that VINS showed better EC50 (2.48 g/mL) value than that of PSAV (6.04 g/mL) and Virchow (6.03 g/mL) antivenoms. Western blotting experiments indicated that all the antivenoms elicited poor binding specificities, especially towards low molecular mass proteins. Second-generation antivenomics studies revealed that VINS antivenom was less efficient to detect many low molecular mass proteins such as three-finger toxins and Kunitz-type serine protease Inhibitors. Taken together, the present study enabled a large-scale characterization of the venom proteome of Naja naja from the Western Ghats and emphasized the need for developing more efficient antivenoms.

HighlightsO_LIProteomics of cobra venom resulted in the identification of 115 proteins representing 17 snake venom protein families.
C_LIO_LIDe novo approaches exclusively yielded 39 peptides harbouring multiple amino acid mutations.
C_LIO_LIGlutathione peroxidase and endonuclease were identified for the first time in Indian cobra venom.
C_LIO_LIIndian polyvalent antivenoms showed varying cross-reactivity towards cobra venom.
C_LIO_LIVINS antivenom was less efficient to detect many low molecular mass proteins (< 20 kDa).
C_LI Pulled Diversification Rates, Lineages-Through-Time Plots and Modern Macroevolutionary Modelling AO_SCPLOWBSTRACTC_SCPLOWEstimating time-dependent rates of speciation and extinction from dated phylogenetic trees of extant species (timetrees), and determining how and why they vary, is key to understanding how ecological and evolutionary processes shape biodiversity. Due to an increasing availability of phylogenetic trees, a growing number of process-based methods relying on the birth-death model have been developed in the last decade to address a variety of questions in macroevolution. However, this methodological progress has regularly been criticised such that one may wonder how reliable the estimations of speciation and extinction rates are. In particular, using lineages-through-time (LTT) plots, a recent study (Louca and Pennell, 2020) has shown that there are an infinite number of equally likely diversification scenarios that can generate any timetree. This has lead to questioning whether or not diversification rates should be estimated at all. Here we summarize, clarify, and highlight technical considerations on recent findings regarding the capacity of models to disentangle diversification histories. Using simulations we demonstrate the characteristics of newly-proposed "pulled rates" and their utility. We recognize that the recent findings are a step forward in understanding the behavior of macroevolutionary modelling, but they in no way suggest we should abandon diversification modelling altogether. On the contrary, the study of macroevolution using phylogenetic trees has never been more exciting and promising than today. We still face important limitations in regard to data availability and methodological shortcomings, but by acknowledging them we can better target our joint efforts as a scientific community. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Identification of druggable host targets needed for SARS-CoV-2 infection by combined pharmacological evaluation and cellular network directed prioritization both in vitro and in vivo. Identification of host factors contributing to replication of viruses and resulting disease progression remains a promising approach for development of new therapeutics. Here, we evaluated 6710 clinical and preclinical compounds targeting 2183 host proteins by immunocytofluorescence-based screening to identify SARS-CoV-2 infection inhibitors. Computationally integrating relationships between small molecule structure, dose-response antiviral activity, host target and cell interactome networking produced cellular networks important for infection. This analysis revealed 389 small molecules, >12 scaffold classes and 813 host targets with micromolar to low nanomolar activities. From these classes, representatives were extensively evaluated for mechanism of action in stable and primary human cell models, and additionally against Beta and Delta SARS-CoV-2 variants and MERS-CoV. One promising candidate, obatoclax, significantly reduced SARS-CoV-2 viral lung load in mice. Ultimately, this work establishes a rigorous approach for future pharmacological and computational identification of novel host factor dependencies and treatments for viral diseases. Artificial reefs geographical location matters more than shape, age and depth for sessile invertebrate colonization in the Gulf of Lion (NorthWestern Mediterranean Sea) AO_SCPLOWBSTRACTC_SCPLOWArtificial reefs (ARs) have been used to support fishing activities. Sessile invertebrates are essential components of trophic networks within ARs, supporting fish productivity. However, colonization by sessile invertebrates is possible only after effective larval dispersal from source populations, usually in natural habitat. While most studies focused on short term colonization by pioneer species, we propose to test the relevance of geographic location, shape, age and depth of immersion on the ARs long term colonization by species found in natural stable communities in the Gulf of Lion. We recorded the presence of five sessile invertebrates species, with contrasting life history traits and regional distribution in the natural rocky habitat, on ARs with different shapes deployed during two immersion time periods (1985 and the 2000s) and in two depth ranges (<20m and >20m). At the local level ([~]5kms), neither shape, depth nor immersion duration differentiated ARs assemblages. At the regional scale (>30kms), colonization patterns differed between species, resulting in diverse assemblages. This study highlights the primacy of geographical positioning over shape, immersion duration and depth in ARs colonization, suggesting it should be accounted for in maritime spatial planning. Growth and division mode plasticity is dependent on cell density in marine-derived black yeasts The diversity and ecological contribution of the fungus kingdom in the marine environment remain under-studied. A recent survey in the Atlantic (Woods Hole, MA, USA) brought to light the diversity and unique biological features of marine fungi. The study revealed that black yeast species undergo an unconventional cell division cycle, which has not been documented in conventional model yeast species such as Saccharomyces cerevisiae (budding yeast) and Schizosaccharomyces pombe (fission yeast). The prevalence of this unusual property is unknown. Here, I collected and identified 65 marine fungi species across 40 genera from the surface ocean water, sediment, and the surface of macroalgae (seaweeds) in the Pacific (Sugashima, Toba, Japan). The Sugashima collection largely did not overlap with the Woods Hole collection and included several unidentifiable species, further illustrating the diversity of marine fungi. Three black yeast species were isolated, two of which were commonly found in Woods Hole (Aureobasidium pullulans, Hortaea werneckii). Surprisingly, their cell division mode was dependent on cell density, and the previously reported unconventional division mode was reproduced only at a certain cell density. For all three black yeast species, cells underwent filamentous growth with septations at low cell density and immediately formed buds at high cell density. At intermediate cell density, two black yeasts (H. werneckii and an unidentifiable species) showed rod cells undergoing septation at the cell equator. In contrast, all eight budding yeast species showed a consistent division pattern regardless of cell density. This study suggests the plastic nature of the growth/division mode of marine-derived black yeast. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Design of a radial multi-offset detection pattern for in vivo phase contrast imaging of the retinal ganglion cells in humans Previous work has shown that multi-offset detection in adaptive optics scanning laser ophthalmoscopy (AOSLO) can be used to image retinal ganglion cells (RGCs) in monkeys and humans. However, though images of RGCs in anesthetized monkeys with high light levels produced high contrast images of RGCs, images from humans failed to reach the same contrast due to several drawbacks in the previous dual-wavelength multi-offset approach. Our aim here was to design and build a multi-offset detection pattern for humans at safe light levels that could reveal the retinal ganglion cell layer neurons with a contrast, robustness and acquisition time approaching results only previously obtained in monkeys. Here, we present a new imaging system using only one light source, compared to the previous dual-wavelength used on monkeys. Our single-wavelength solution allows for increased light power and eliminates problematic chromatic aberrations. Then, we demonstrate that a radial multi-offset detection pattern with an offset distance of 8-10 Airy Disk Diameter (ADD) is optimal to detect photons multiply scattered in all directions from RGCs thereby enhancing their contrast. This new setup and image processing pipeline led to improved imaging of retinal ganglion cells using multi-offset imaging in AOSLO. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Ecological interactions in breast cancer: Cell facilitation promotes growth and survival under drug pressure The interplay of positive and negative interactions between drug sensitive and resistant cells determines the efficacy of treatment in heterogeneous cancer cell populations. We developed isogenic estrogen receptor positive (ER+) breast cancer cell lineages sensitive and resistant to ribociclib-induced CDK4/6 inhibition to investigate cell interactions under selective pressure. During treatment with ribociclib alone or in combination with endocrine therapies, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays detected estrone, a less active metabolite, in medium taken from each lineage but detected highly active estradiol only from resistant cells. Because sensitive cells are more dependent on estrogen signaling than resistant cells, they benefit from the increase in local estradiol from resistant cells, leading to facilitated growth when grown under treatment in coculture. We developed a suite of mathematical models to quantify the strength of competition and facilitation between cell lines and evaluate the effects of treatments that modify these interactions. These analyses support the conclusion that resistant cell lineages facilitate growth of sensitive lineages during therapy through the increased production and sharing of local estradiol and themselves suffer from increased competition and suppression as a result. These models show that blocking facilitation has the potential to control both resistant and sensitive cell populations and inhibit the emergence of a refractory population. This combination of experiments and models shows that interactions within heterogeneous cancer cell populations can combine positive and negative interactions to shape the dynamics of resistance. Mapping densely packed GPIIb/IIIa receptors in murine blood platelets with expansion microscopy Interrogating small platelets and their densely packed, highly abundant receptor landscape is key to understand platelet clotting, a process that can save lives when stopping blood loss after an injury, but also kill when causing heart attack, stroke or pulmonary embolism. The underlying key receptor distributions and interactions, in particular the relevance of integrin clustering, are not fully understood is because of highly abundant and densely distributed GPIIb/IIIa receptors. This makes receptor distributions difficult to assess even by super-resolution fluorescence microscopy. Here, we combine dual-color expansion and confocal microscopy with colocalization analysis to assess platelet receptor organization without the need of a super-resolution microscope. We show that 4x expansion is highly straight-forward for super-resolution microscopy of platelets, while 10x expansion provides higher precision at the price of increased efforts in sample preparation and imaging. Quantifying various receptor colocalization scenarios we demonstrate that expansion microscopy can pinpoint receptor distributions and interactions in resting and activated platelets being superior to conventional methods that fail in such dense 3D scenarios with highly abundant receptors. We reveal the presence of GPIIb/IIIa clusters in resting platelets, which are not affected by platelet activation indicating that they contribute to the rapid platelet response during platelet clotting.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/431449v3_ufig1.gif" ALT="Figure 1">
View larger version (29K):
org.highwire.dtl.DTLVardef@c4e38forg.highwire.dtl.DTLVardef@37c1adorg.highwire.dtl.DTLVardef@8c8597org.highwire.dtl.DTLVardef@196bd69_HPS_FORMAT_FIGEXP  M_FIG C_FIG S-acylation stabilizes ligand-induced receptor kinase complex formation during plant pattern-triggered immune signalling. Plant receptor kinases are key transducers of physical extracellular stimuli, such as the presence of beneficial or pathogenic microbes or secreted signalling molecules. Receptor kinases are regulated by numerous post-translational modifications. Here, using the bacterial flagellin perceiving receptor kinase FLS2, we show that S-acylation at an evolutionarily conserved cysteine is crucial for function. S-acylation involves the addition of long-chain fatty acids to cysteine residues within proteins, altering their biophysical properties and behaviour within the membrane environment. We observe S-acylation of FLS2 at C-terminal kinase domain cysteine residues within minutes of treatment with flg22 ligand, and in a BAK1 co-receptor dependent manner. We demonstrate that S-acylation is essential for FLS2-mediated immune signalling, including anti-bacterial immunity. Similarly, mutating the corresponding conserved cysteine residue in the immune receptor kinase EFR supressed elf18 mediated signalling. Biochemical analysis of unstimulated and activated FLS2 containing complexes using detergents and native membrane DIBMA nanodiscs indicates that S-acylation assists the stabilization of activated receptor kinase complexes withing the membrane environment to increase signalling efficiency. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

MethodsWe propose a two-step approach to the analysis of a genetic association study: first, a set of variants that show evidence of association with the trait is used to estimate m; and second, the estimated m is used for log-F -penalized logistic regression analyses of all variants using data augmentation with standard software. Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation.

ResultsWe evaluate the statistical properties of our proposed two-step method and compared its performance to other shrinkage methods by a simulation study. Our simulation studies suggest that the proposed log-F -penalized approach has lower bias and mean squared error than other methods considered. We also illustrate the approach on data from a study of genetic associations with "super senior" cases and middle aged controls.

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach. Feline tooth resorption findings from a questionnaire survey on 8115 Finnish cats and a case-control study for a more defined population drawn from the survey Tooth resorption (TR) is one of the most common dental diseases in cats. It is a painful disease characterised by progressive dental destruction, which eventually results in loss of teeth. The aetiology of the disease remains unclear, but associations with old age, breed, other oral and dental diseases, and certain environmental factors have been suspected. We collected health and environmental information of 8115 Finnish cats from 41 breeds through an online survey for cat owners to study TR in Finland with an observational study. The frequency of TR that the owner reported as veterinarian-diagnosed was 3.9% in the entire data (316/8115) and 15% in cats that the owner reported as having veterinarian-diagnosed oral or dental disease (316/2070). We determined the risk factors and breed variation of feline TR by logistic regression with the entire data and a case-control study in a more defined population drawn from the entire data. In the entire data, we defined those cats that the owners had reported as being diagnosed with TR by a veterinarian as TR-cats and compared them to all other cats. In the case-control study, we included only cats with owner-reported veterinarian-diagnosed oral and dental diseases. We defined cats with TR-diagnosis made under sedation as TR-cases. Other veterinarian-diagnosed TR-cats were excluded. Cats with other oral and dental diseases were used as controls. The model with the entire population included 308 TR-cats compared with 7508 cats, and the case-control study included 198 TR-cats and 1683 controls. Although the diagnoses were reportedly made by a veterinarian, the owner answered the survey and might have understood, remembered, or interpreted the diagnoses in a way that could affect the results. The results indicated an increasing risk of TR with age. Dental calculus, gingivitis, and periodontitis were potential risk factors for TR. These findings and the interaction between dental calculus and gingivitis suggest that inflammatory changes caused by dental calculus increase the risk of TR. Keeping food available constantly was a potential protective factor. We found that Cornish Rex, European, and Ragdoll breeds were at higher risk for TR. The observed differences between breeds highlight a genetic contribution. Single molecule studies reveal branched pathways for activator-dependent assembly of RNA polymerase II pre-initiation complexes RNA polymerase II (Pol II) transcription reconstituted from purified factors suggests pre-initiation complexes (PICs) can assemble by sequential incorporation of factors at the TATA box. However, these basal transcription reactions are generally independent of activators and co-activators. To study PIC assembly under more realistic conditions, we used single-molecule microscopy to visualize factor dynamics during activator-dependent reactions in nuclear extracts. Surprisingly, Pol II, TFIIF, and TFIIE can pre-assemble on enhancer-bound activators before loading into PICs, and multiple Pol II complexes can bind simultaneously to create a localized cluster. Unlike TFIIF and TFIIE, TFIIH binding is singular and dependent on the basal promoter. Activator-tethered factors exhibit dwell times on the order of seconds. In contrast, PICs can persist on the order of minutes in the absence of nucleotide triphosphates, although TFIIE remains unexpectedly dynamic even after TFIIH incorporation. Our kinetic measurements lead to a new branched model for activator-dependent PIC assembly.

HIGHLIGHTSSingle molecule microscopy reveals unexpected dynamics of RNA Pol II and GTFs

Multiple Pol IIs cluster on UAS/enhancer-bound activators before binding the core promoter

Pol II, TFIIF, and TFIIE, but not TFIIH, can pre-assemble at the UAS/enhancer

Activators increase the rates of Pol II and GTF association with DNA

eTOC BlurbSingle-molecule microscopy experiments by Baek et al. show that RNA polymerase II and basal transcription factors TFIIF and TFIIE preassemble on UAS/enhancer-bound activators, poised for loading into initiation complexes with TFIIH at the core promoter. Transcription activators kinetically enhance factor recruitment, creating a localized cluster of polymerases at the UAS/enhancer. A protein microarray-based in vitro transglutaminase assay platform for epitope mapping and peptide discovery: implication for transglutaminase-mediated immunodominant determination Transglutaminases (TGs) are a family of crosslinking enzymes catalyzing the formation of intra- and inter-molecular glutamine-lysine isopeptide bonds in a calcium dependent manner. Activation of transglutaminases is pathogenically associated with severe human diseases including neurodegenerations, cardiovascular diseases, and autoimmune diseases. Although continuous efforts determining the enzymes substrate preference have been witnessed, a high-throughput assay platform with the "omic" efficiency is still missing for the global identification of substrate-specific TG modification sites. In this study we report a protein microarray-based in vitro TG assay platform for rapid and large-scale (up to 30000 reactions per chip) determination of the glutamine (Q)-bearing TG modification motifs. With this platform we identified the Q16 in superoxide dismutase 1 and Q109 in alpha-synuclein as the primary modification sites for tissue transglutaminase (TG2), the most ubiquitous member of the enzyme family. Of particular interest, we found a close match between the modification motifs and published vaccine epitope sequences in alpha-synuclein, implying an essential and intrinsic role transglutaminase might play in the determination of immunodominant epitopes. Our data collectively suggest the glutamine and its follow-up five residues on the C terminal of a protein compose a minimal determinant motif for TG2 modification and the TG2 modification motifs determined by our platform could finally correspond to the substrates epitope sequences in antigen processing. To screen for site-specific interfering peptides and assist gene editing-based protein engineering, we optimized through onchip amino-acid scanning the TG2 modification motif QQIV in the extracellular matrix protein fibronectin and obtained 14 variants with significantly higher TG2 reactivity that might serve as the competitive inhibitor peptides and 1 with lower reactivity. We further confirmed this optimization approach with 12-mer peptides, the longest ones that could be synthesized on the chip. Taken together, our synthetic transglutaminase assay platform might be able to deliver a precise epitope blueprint for immunotherapeutic targeting and provide proof-of-concept and directional studies for TG-based peptide discovery and protein design. Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements.

In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification. High-Potency Polypeptide-based Inhibition of Enveloped-virus Glycoproteins Specific manipulation of proteins post-translationally remains difficult. Here we report results of a general approach that uses a partial sequence of a protein to efficiently modulate the expression level of the native protein. When applied to coronavirus, human immunodeficiency virus, Ebolavirus, respiratory syncytial virus and influenza virus, polypeptides containing highly conserved regions of the viral glycoproteins potently diminished expression of the respective native proteins. In the cases of coronavirus and influenza virus where multiple strains were tested, the polypeptides were equally effective against glycoproteins of other coronavirus and influenza strains with sequence identity as low as 27%, underscoring their high insensitivity to mutations. Thus, this method provides a platform for developing high-efficacy broad-spectrum anti-viral inhibitors, as well as a new way to alter expression of essentially any systems post-translationally. A cell cycle-dependent GARP-like transcriptional repressor regulates the initiation of differentiation in Giardia lamblia Transcriptional regulation of differentiation is critical for parasitic pathogens to adapt to environmental changes and regulate transmission. In response to encystation stimuli, Giardia lamblia cells shift from G1+S phase of the cell cycle to G2+M. By 2-4 hours, cyst wall proteins are upregulated, indicating that key regulatory steps occur within the first four hours of encystation. However, all characterized transcription factors (TFs) in Giardia have only been investigated at later time points of encystation. How TFs initiate encystation and link it to the cell cycle remains enigmatic. Here, we systematically screened six putative early upregulated TFs for nuclear localization, established their dynamic expression profiles, and determined their functional role in regulating encystation. We found a critical repressor, GLP4 that increases rapidly after 30 min of encystation stimuli and downregulates encystation specific markers, including Cyst Wall Proteins (CWPs) and enzymes in the cyst N-acetyl galactosamine (GalNAc) pathway. Depletion of GLP4 increases cyst production. Importantly, we observe that G2+M cells exhibit higher levels of CWP1 resulting from the activation of MYB2, a TF previously linked to encystation in Giardia. GLP4 upregulation occurs in G1+S cells, suggesting a role in repressing MYB2 and encystation specific genes in the G1+S phase of the cell cycle. Furthermore, we demonstrate that depletion of GLP4 upregulates MYB2 and promotes encystation while overexpression of GLP4 downregulates MYB2 and represses encystation. Together, these results suggest that Giardia employs a dose-dependent transcriptional response that involves the cell cycle regulated repressor GLP4 to orchestrate MYB2 and entry into the encystation pathway.

ImportanceTransition between life cycle stages is a common feature among parasitic pathogens and its regulation must be optimized to balance persistence of infection with transmission. The early transcription factors (TFs) regulating commitment to differentiate are totally unknown in Giardia. In this work, we identified GLP4, a previously uncharacterized GARP-like TF, as an early-acting transcriptional repressor that inhibits G1+S cells from entering the encystation pathway. GLP4 is therefore a key regulator controlling the balance between proliferative growth and terminal differentiation into infective cysts. Mouse lemur, a new primate model to investigate cardiac pacemaker activity. BackgroundGray mouse lemurs (Microcebus murinus) are one of the smallest and most ancestral primates known. Their size falls in between that of mice and rats, and their genetic proximity to humans makes them an emerging model to study age-related neurodegeneration. Since Microcebus murinus replicates similar senescence processes of humans, it constitutes a useful model also for studying cardiovascular dysfunctions. However, its cardiac physiology is unknown. Thus, we investigated sinoatrial node (SAN) pacemaker activity of mouse lemurs, presenting the first characterization of heart automaticity in nonhuman primates.

Methods and ResultsWe recorded the heart automaticity in freely moving mouse lemurs and in their SAN tissues and pacemaker myocytes. Mouse lemurs have a heart rate (HR) in between those of mice and rats and a similar generation of electrical impulses in the SAN tissue. Conversely, their ventricular depolarization is more similar to large mammals. Mouse lemur SAN myocytes express the main pacemaker currents at densities similar to mice: the hyperpolarization-activated current (If) and the L-type (ICa,L) and T-type (ICa,T) calcium currents. Moreover, mouse lemur SAN myocytes display spontaneous ryanodine receptor (RyR)-dependent Ca2+ transients. Using muscle-derived stem cells (MDSCs) from the Microcebus murinus skeletal muscle, we also differentiated pacemaker-like (PML) cells showing spontaneous automaticity and expressing markers of native SAN myocytes (HCN4 and connexin-45).

ConclusionsIn conclusion, our characterization of heart automaticity in Microcebus murinus provides new opportunities for comparative cardio-physiology studies in primates and with humans, and for pharmacologic testing of molecules that could assist in modulating age-related dysfunctions of automaticity.