The TR Prize are monthly awards for the best new research.

Below is this month's biology research from Biorxiv and Arxiv. TR Prizes based on your donations and peer reviews of these works are given at the end of each month.

1. Higher-order chromatin organization defines PR and PAX2 binding to regulate endometrial cancer cell gene expression

20 August 2019 | Biorxiv link | Write review

Estrogen (E2) and Progesterone (Pg) via their specific receptors, ER and PR respectively, are major determinants in the development and progression of endometrial malignancies. We have studied how E2 and the synthetic progestin R5020 affect genomic function in Ishikawa endometrial cancer cells. Using ChIPseq in cells exposed to the corresponding hormones, we identified cell specific binding sites for ER (ERbs) and PR (PRbs), mostly binding to independent sites and both adjacent to PAXbs. Long-range interactions (HiC) showed enrichment of PRbs and PAXbs, which we call progestin control regions (PgCRs) inside TADs with differentially progestin-regulated genes. Effects of hormone treatments on gene expression were detected by RNAseq. PgCRs correlate with open chromatin independently of hormonal stimuli. In summary, endometrial response to progestins in differentiated endometrial tumor cells results in part from binding of PR to compartmentalized PgCRs in hormone-independent open chromatin, which include binding of partner transcription factors, in particular PAX2.

2. An Anisotropic Interaction Model for Simulating Fingerprints

20 August 2019 | Arxiv link | Write review

Evidence suggests that both the interaction of so-called Merkel cells and the epidermal stress distribution play an important role in the formation of fingerprint patterns during pregnancy. To model the formation of fingerprint patterns in a biologically meaningful way these patterns have to become stationary. For the creation of synthetic fingerprints it is also very desirable that rescaling the model parameters leads to rescaled distances between the stationary fingerprint ridges. Based on these observations, as well as the model introduced by K\"ucken and Champod we propose a new model for the formation of fingerprint patterns during pregnancy. In this anisotropic interaction model the interaction forces not only depend on the distance vector between the cells and the model parameters, but additionally on an underlying tensor field, representing a stress field. This dependence on the tensor field leads to complex, anisotropic patterns. We study the resulting stationary patterns both analytically and numerically. In particular, we show that fingerprint patterns can be modeled as stationary solutions by choosing the underlying tensor field appropriately.

3. Structure of S. pombe telomerase protein Pof8 C-terminal domain is an xRRM conserved among LARP7 proteins

20 August 2019 | Biorxiv link | Write review

La related proteins group 7 (LARP7) are a class of RNA chaperones that bind the 3' ends of RNA and are constitutively associated with their specific target RNAs. In metazoa, Larp7 binds to the long non-coding 7SK RNA as a core component of the 7SK RNP, a major regulator of eukaryotic transcription. In ciliates, a LARP7 protein (p65 in Tetrahymena) is a core component of telomerase, an essential ribonucleoprotein complex that maintains the DNA length at eukaryotic chromosome ends. p65 is important for the ordered assembly of telomerase RNA (TER) with telomerase reverse transcriptase (TERT). Although a LARP7 as a telomerase holoenzyme component was initially thought to be specific to ciliate telomerases, Schizosaccharomyces pombe Pof8 was recently identified as a LARP7 protein and a core component of fission yeast telomerase essential for biogenesis. There is also evidence that human Larp7 associates with telomerase. LARP7 proteins have conserved N-terminal La motif and RRM1 (La module) and C-terminal RRM2 with specific RNA substrate recognition attributed to RRM2, first structurally characterized in p65 as an atypical RRM named xRRM. Here we present the X-ray crystal structure and NMR studies of S. pombe Pof8 RRM2. Sequence and structure comparison of Pof8 RRM2 to p65 and hLarp7 xRRMs reveals conserved features for RNA binding with the main variability in the length of the non-canonical helix 3. This study shows that Pof8 has conserved xRRM features, providing insight into TER recognition and the defining characteristics of the xRRM.

4. Input-output equivalence and identifiability: some simple generalizations of the differential algebra approach

20 August 2019 | Arxiv link | Write review

In this paper, we give an overview of the differential algebra approach to identifiability, and then note a very simple observation about input-output equivalence and identifiability, that describes the identifiability equivalence between input-output equivalent models. We then give several simple consequences of this observation that can be useful in showing identifiability, including examining non-first order ODE models, nondimensionalization and rescaling, model reducibility, and a modular approach to evaluating identifiability. We also examine how input-output equivalence can allow us to generate input output equations in the differential algebra approach through a wider range of methods (e.g. substitution and differential or standard Groebner basis approaches).

5. Optogenetic inhibition of Delta reveals digital Notch signaling output during tissue differentiation

19 August 2019 | Biorxiv link | Write review

Spatio-temporal regulation of signalling pathways plays a key role in generating diverse responses during the development of multicellular organisms. The role of signal dynamics in transferring signalling information in vivo is incompletely understood. Here we employ genome engineering in Drosophila melanogaster to generate a functional optogenetic allele of the Notch ligand Delta (opto-Delta), which replaces both copies of the endogenous wild type locus. Using clonal analysis, we show that optogenetic activation blocks Notch activation through cis-inhibition in signal-receiving cells. Signal perturbation in combination with quantitative analysis of a live transcriptional reporter of Notch pathway activity reveals differential tissue- and cell-scale regulatory modes. While at the tissue-level the duration of Notch signalling determines the probability with which a cellular response will occur, in individual cells Notch activation acts through a switch-like mechanism. Thus, time confers regulatory properties to Notch signalling that exhibit integrative digital behaviours during tissue differentiation.

6. Path probability density functions for semi-Markovian random walks

19 August 2019 | Arxiv link | Write review

In random walks, the path representation of the Green's function is an infinite sum over the length of path probability density functions (PDFs). Here we derive and solve, in Laplace space, the recursion relation for the n order path PDF for any arbitrarily inhomogeneous semi-Markovian random walk in a one-dimensional (1D) chain of L states. The recursion relation relates the n order path PDF to L/2 (round towards zero for an odd L) shorter path PDFs, and has n independent coefficients that obey a universal formula. The z transform of the recursion relation straightforwardly gives the generating function for path PDFs, from which we obtain the Green's function of the random walk, and derive an explicit expression for any path PDF of the random walk. These expressions give the most detailed description of arbitrarily inhomogeneous semi-Markovian random walks in 1D.

7. PuMA: a papillomavirus genome annotation tool

19 August 2019 | Biorxiv link | Write review

High-throughput sequencing technologies provide unprecedented power to identify novel viruses from a wide variety of (environmental) samples. The field of 'viral metagenomics' has dramatically expanded our understanding of viral diversity. Viral metagenomic approaches imply that many novel viruses will not be described by researchers who are experts on the genomic organization of that virus. There is a need to develop analytical approaches to reconstruct, annotate, and classify viral genomes. We have developed the papillomavirus annotation tool (PuMA) to provide researchers with a convenient and reproducible method to annotate novel papillomaviruses. PuMA provides an accessible method for automated papillomavirus genome annotation. PuMA currently has a 98% accuracy when benchmarked against the 481 reference genomes in the papillomavirus episteme (PaVE). Finally, PuMA was used to annotate 168 newly isolated papillomaviruses, and successfully annotated 1424 viral features. To demonstrate its general applicability, we developed a version of PuMA that can annotate polyomaviruses. Availability and Implementation: PuMA is available on GitHub (https://github.com/KVD-lab/puma) and through the iMicrobe online environment (https://www.imicrobe.us/#/apps/puma).

8. Relationship between cellular response and behavioral variability in bacterial chemotaxis

19 August 2019 | Arxiv link | Write review

Bacterial chemotaxis in Escherichia coli is a canonical system for the study of signal transduction. A remarkable feature of this system is the coexistence of precise adaptation in population with large fluctuating cellular behavior in single cells (Korobkova et al. 2004, Nature, 428, 574). Using a stochastic model, we found that the large behavioral variability experimentally observed in non-stimulated cells is a direct consequence of the architecture of this adaptive system. Reversible covalent modification cycles, in which methylation and demethylation reactions antagonistically regulate the activity of receptor-kinase complexes, operate outside the region of first-order kinetics. As a result, the receptor-kinase that governs cellular behavior exhibits a sigmoidal activation curve. This curve simultaneously amplifies the inherent stochastic fluctuations in the system and lengthens the relaxation time in response to stimulus. Because stochastic fluctuations cause large behavioral variability and the relaxation time governs the average duration of runs in response to small stimuli, cells with the greatest fluctuating behavior also display the largest chemotactic response. Finally, Large-scale simulations of digital bacteria suggest that the chemotaxis network is tuned to simultaneously optimize the random spread of cells in absence of nutrients and the cellular response to gradients of attractant.

9. Modeling and treating GRIN2A developmental and epileptic encephalopathy in mice

18 August 2019 | Biorxiv link | Write review

NMDA receptors (NMDAR) play crucial roles in excitatory synaptic transmission. Rare variants of GRIN2A, which encodes the GluN2A NMDAR subunit, are associated with several intractable neurodevelopmental disorders, including developmental and epileptic encephalopathy (DEE). A de novo missense variant, p.Ser644Gly (c.1930A>G), was identified in a child with DEE, and Grin2a knockin mice were generated to model and extend understanding of this intractable childhood disease. Homozygous and heterozygous mutant mice exhibit altered hippocampal morphology at two weeks of age, and homozygotes exhibit lethal tonic-clonic seizures in the third week. Heterozygous adult mice display a variety of distinct features, including resistance to electrically induced partial seizures, as well as hyperactivity and repetitive and reduced anxiety behaviors. Multielectrode recordings of mutant neuronal networks reveal hyperexcitability and altered bursting and synchronicity. When expressed in heterologous cells, mutant receptors exhibit enhanced NMDAR agonist potency and slow deactivation following rapid removal of glutamate, as occurs at synapses. Consistent with these observations, NMDAR-mediated synaptic currents in hippocampal slices from mutant mice show a prolonged deactivation time course. Standard antiepileptic drug monotherapy was ineffective in the patient, but combined treatment of NMDAR antagonists with antiepileptic drugs substantially reduced the seizure burden albeit without appreciable developmental improvement. Chronic treatment of homozygous mutant mouse pups with NMDAR antagonists delayed the onset of lethal seizures but did not prevent them. These studies illustrate the power of modeling severe neurodevelopmental seizure disorders using multiple experimental modalities and suggest their extended utility in identifying and evaluating new therapies.

10. Complexation of DNA with Cationic Surfactant

18 August 2019 | Arxiv link | Write review

Transfection of an anionic polynucleotide through a negatively charged membrane is an important problem in genetic engineering. The direct association of cationic surfactant to DNA decreases the effective negative charge of the nucleic acid, allowing the DNA-surfactant complex to approach a negatively charged membrane. The paper develops a theory for solutions composed of polyelectrolyte, salt, and ionic surfactant. The theoretical predictions are compared with the experimental measurements.

11. Characterizing allele-by-environment interactions using maize introgression lines

18 August 2019 | Biorxiv link | Write review

Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to allele-by-environment interactions. To study potential patterns of allele-by-environment interactions, fifteen near-isogenic lines (NILs) with >90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess allele-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the allele-by-environment interaction varies across traits. Some introgressed segments were more prone to genotype-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of allele-by-environment interaction is useful in considerations of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments.

12. Bacterial evolution and the Bak-Sneppen model

18 August 2019 | Arxiv link | Write review

Recently, Lenski et al \cite{Elena,Lenski,Travisano} have carried out several experiments on bacterial evolution. Their findings support the theory of punctuated equilibrium in biological evolution. They have further quantified the relative contributions of adaptation, chance and history to bacterial evolution. In this Brief Report, we show that a modified M-trait Bak-Sneppen model can explain many of the experimental results in a qualitative manner.

13. A personalised approach for identifying disease-relevant pathways in heterogeneous diseases

17 August 2019 | Biorxiv link | Write review

Numerous time-course gene expression datasets have been curated for studying the biological dynamics that drive disease progression; and nearly as many methods have been proposed to analyse them. However, barely any method exists that can appropriately model time-course data and at the same time account for heterogeneity that entails many complex diseases. Most methods manage to fulfil either one of those qualities, but not both. The lack of appropriate methods hinders our capability of understanding the disease process and pursuing preventive or curative treatments. Here, we present a method that models time-course data in a personalised manner, i.e. for each case-control pair individually, using Gaussian processes in order to identify differentially expressed genes (DEGs); and combines the lists of DEGs on a pathway-level using a permutation-based empirical hypothesis testing in order to overcome gene-level variability and inconsistencies prevalent to heterogeneous datasets from complex diseases. Our method can be applied to study the time-course dynamics as well as specific time-windows of heterogeneous diseases. We apply our personalised approach on two longitudinal type 1 diabetes (T1D) datasets to determine perturbations that take place during early prognosis of the disease as well as in time-windows before seroconversion and clinical onset of T1D. By comparing to non-personalised methods, we demonstrate that our approach is biologically motivated and can reveal more insights into progression of heterogeneous diseases. With its robust capabilities of identifying immunologically interesting and disease-relevant pathways, our approach could be useful for predicting certain events in the progression of heterogeneous diseases and even biomarker identification.

14. Visualizing evidence for Alzheimer's disease in deep neural networks trained on structural MRI data

17 August 2019 | Arxiv link | Write review

Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer's disease (AD) detection based on structural magnetic resonance imaging (MRI) data. However, the network decisions are often perceived as being highly non-transparent making it difficult to apply these algorithms in clinical routine. In this study, we propose using layer-wise relevance propagation (LRP) to visualize convolutional neural network decisions for AD based on MRI data. Similarly to other visualization methods, LRP produces a heatmap in the input space indicating the importance of each voxel contributing to the final classification outcome. In contrast to susceptibility maps produced by guided backpropagation ("Which change in voxels would change the outcome most?"), the LRP method is able to directly highlight positive contributions to the network classification in the input space. Thus, the highlighted areas can be interpreted as the 'positive evidence' used by the network for deciding whether an individual has AD. We find that this LRP-evidence indeed fulfills those expectations that one would have towards AD evidence: (1) it is very specific for individuals ("Why does this person have AD?") with high inter-patient variability, (2) there is very little evidence for AD in healthy controls and (3) areas that exhibit a lot of evidence correlate well with what is known from literature. To quantify the latter, we compute size-corrected metrics of the summed evidence per brain area, e.g. the 'evidence density' or 'evidence gain'. Although these metrics produce very individual 'fingerprints' of relevance patterns for AD patients, a lot of importance is put on areas in the temporal lobe including hippocampus and amygdala. We conclude that LRP provides a powerful tool for assisting clinicians in finding evidence for AD (and potentially other diseases) in structural MRI data.

15. An amino-terminal threonine/serine motif is necessary for activity of the Crp/Fnr homolog, MrpC, and for Myxococcus xanthus developmental robustness

17 August 2019 | Biorxiv link | Write review

The Crp/Fnr family of transcriptional regulators play central roles in transcriptional control of diverse physiological responses. Activation of individual family members is controlled by a surprising diversity of mechanisms tuned to the particular physiological responses or lifestyles that they regulate. MrpC is a Crp/Fnr homolog that plays an essential role in controlling the Myxococcus xanthus developmental program. A long-standing model proposed that MrpC activity is controlled by the Pkn8/Pkn14 serine/threonine kinase cascade which phosphorylates MrpC on threonine residue(s) located in its extreme amino terminus. In this study, we demonstrate that a stretch of consecutive threonine and serine residues, T21 T22 S23 S24, is necessary for MrpC activity by promoting efficient DNA binding. Mass spectrometry analysis indicated the TTSS motif is not directly phosphorylated by Pkn14 in vitro but is necessary for efficient Pkn14-dependent phosphorylation on several residues in the remainder of the protein. Pkn8 and Pkn14 kinase activities do not play obvious roles in controlling MrpC activity in wild type M. xanthus under laboratory conditions, but likely modulate MrpC DNA binding in response to unknown environmental conditions. Interestingly, mutational analysis of the TTSS motif caused non-robust developmental phenotypes, revealing that MrpC plays a role in developmental buffering.

16. Dynamics and computation in mixed networks containing neurons that accelerate towards spiking

17 August 2019 | Arxiv link | Write review

Networks in the brain consist of different types of neurons. Here we investigate the influence of neuron diversity on the dynamics, phase space structure and computational capabilities of spiking neural networks. We find that already a single neuron of a different type can qualitatively change the network dynamics and that mixed networks may combine the computational capabilities of ones with a single neuron type. We study inhibitory networks of concave leaky (LIF) and convex "anti-leaky" (XIF) integrate-and-fire neurons that generalize irregularly spiking non-chaotic LIF neuron networks. Endowed with simple conductance-based synapses for XIF neurons, our networks can generate a balanced state of irregular asynchronous spiking as well. We determine the voltage probability distributions and self-consistent firing rates assuming Poisson input with finite size spike impacts. Further, we compute the full spectrum of Lyapunov exponents (LEs) and the covariant Lyapunov vectors (CLVs) specifying the corresponding perturbation directions. We find that there is approximately one positive LE for each XIF neuron. This indicates in particular that a single XIF neuron renders the network dynamics chaotic. A simple mean-field approach, which can be justified by properties of the CLVs, explains the finding. As an application, we propose a spike-based computing scheme where our networks serve as computational reservoirs and their different stability properties yield different computational capabilities.

17. Screening and identification of MicroRNAs expressed in perirenal adipose tissue during rabbit growth

16 August 2019 | Biorxiv link | Write review

MiRNAs regulate adipose tissue development, which are closely related to subcutaneous and intramuscular fat deposition and adipocyte differentiation. As an important economic and agricultural animal, rabbits have low adipose tissue deposition and are an ideal model to study adipose regulation. However, the miRNAs related to fat deposition during the growth and development of rabbits are poorly defined. In this study, miRNA-sequencing and bioinformatics analyses were used to profile the miRNAs in rabbit perirenal adipose tissue at 35, 85 and 120 days post-birth. Differentially expressed (DE) miRNAs between different stages were identified by DEseq in R. Target genes of DE miRNAs were predicted by TargetScan and miRanda. To explore the functions of identified miRNAs, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Approximately 1.6 GB of data was obtained by miRNA-seq. A total of 987 miRNAs (780 known and 207 newly predicted) and 174 DE miRNAs were identified. The miRNAs ranged from 18nt to 26nt. GO enrichment and KEGG pathway analyses revealed that the target genes of the DE miRNAs were mainly involved in zinc ion binding, regulation of cell growth, MAPK signaling pathway, and other adipose hypertrophy-related pathways. Six DE miRNAs were randomly selected and their expression profiles were validated by q-PCR. In summary, we provide the first report of the miRNA profiles of rabbit adipose tissue during different growth stages. Our data provide a theoretical reference for subsequent studies on rabbit genetics, breeding and the regulatory mechanisms of adipose development.

18. Minimal model of transcriptional elongation processes with pauses

16 August 2019 | Arxiv link | Write review

Fundamental biological processes such as transcription and translation, where a genetic sequence is sequentially read by a macromolecule, have been well described by a classical model of non-equilibrium statistical physics, the totally asymmetric exclusion principle (TASEP). This model describes particles hopping between sites of a one-dimensional lattice, with the particle current determining the transcription or translation rate. An open problem is how to analyze a TASEP where particles can pause randomly, as has been observed during transcription. In this work, we report that surprisingly, a simple mean-field model predicts well the particle current for all values of the average pause duration, using a simple description of blocking behind paused particles.

19. Enduring consequences of perinatal fentanyl exposure in mice

16 August 2019 | Biorxiv link | Write review

Opioid use by pregnant women is an understudied consequence associated with the opioid epidemic, resulting in a rise in the incidence of neonatal opioid withdrawal syndrome (NOWS), and lifelong neurobehavioral deficits that result from perinatal opioid exposure. There are few preclinical models that accurately recapitulate human perinatal drug exposure, and none focus on fentanyl, a potent synthetic opioid that is a leading driver of the opioid epidemic. To more readily investigate the consequences of perinatal opioid exposure, we administered fentanyl to mouse dams in their drinking water throughout gestation and until litters are weaned at postnatal day (PD) 21. First, we found that fentanyl-exposed dams delivered smaller litters, when compared to saccharine-exposed control dams. Twenty-four hours after weaning and drug cessation, fentanyl-exposed mice exhibited signs of somatic withdrawal, and sex-specific weight fluctuations that normalized in adulthood. At adolescence (PD 35) they displayed elevated anxiety-like behaviors and decreased grooming, assayed in the elevated plus maze and sucrose splash tests. Finally, in adulthood (PD 55) they displayed impaired performance in a two-tone auditory discrimination task. Collectively, our findings suggest that we have developed an effective rodent model of NOWS, with high face validity that will allow studying changes associated with perinatal fentanyl exposure across the lifespan.

20. Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks

16 August 2019 | Arxiv link | Write review

How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.

21. Selectivity Filter Instability Dominates the Low Intrinsic Activity of the TWIK-1 K2P K+ Channel

15 August 2019 | Biorxiv link | Write review

The functional properties of the TWIK-1 (KCNK1) Two-Pore Domain (K2P) K+ channel remain poorly characterized due to the very low levels of functional activity it produces when heterologously expressed. Several underlying reasons have been proposed including retention in intracellular organelles, inhibition by post-translational sumoylation, a hydrophobic barrier within the pore, and a low intrinsic open-probability of the selectivity filter (SF) gate. By evaluating these different mechanisms, we found the latter to dominate this low intrinsic functional activity and investigated the underlying mechanism. The low activity of the SF gate appears to result from the inefficiency of K+ in stabilizing an active (i.e. conductive) SF conformation, while other permeant ion species such as Rb+, NH4+ and Cs+ strongly promote a pH-dependent activated conformation. Furthermore, while many K2P channels are activated by membrane depolarization via a SF-mediated gating mechanism, only very strong, non-physiological depolarization produces voltage-dependent activation and the channel displays unusual inactivation kinetics. Remarkably, we observed that TWIK-1 Rb+ currents were potently inhibited by intracellular K+ (IC50 = 2.8 mM). TWIK-1 therefore displays unique SF gating properties amongst the family of K2P channels. In particular, the apparent instability of the conductive conformation of the TWIK-1 SF in the presence of K+ appears to dominate the low levels of intrinsic functional activity observed when the channel is expressed at the cell surface.

22. A biologically motivated three-species exclusion model: effects of leaky scanning and overlapping genes on initiation of protein synthesis

15 August 2019 | Arxiv link | Write review

Totally asymmetric simple exclusion process (TASEP) was originally introduced as a model for the traffic-like collective movement of ribosomes on a messenger RNA (mRNA) that serves as the track for the motor-like forward stepping of individual ribosomes. In each step, a ribosome elongates a protein by a single unit using the track also as a template for protein synthesis. But, pre-fabricated, functionally competent, ribosomes are not available to begin synthesis of protein; a subunit directionally scans the mRNA in search of the pre-designated site where it is supposed to bind with the other subunit and begin the synthesis of the corresponding protein. However, because of `leaky' scanning, a fraction of the scanning subunits miss the target site and continue their search beyond the first target. Sometimes such scanners successfully identify the site that marks the site for initiation of the synthesis of a different protein. In this paper, we develop an exclusion model, with three interconvertible species of hard rods, to capture some of the key features of these biological phenomena and study the effects of the interference of the flow of the different species of rods on the same lattice. More specifically, we identify the meantime for the initiation of protein synthesis as appropriate mean {\it first-passage} time that we calculate analytically using the formalism of backward master equations. In spite of the approximations made, our analytical predictions are in reasonably good agreement with the numerical data that we obtain by performing Monte Carlo simulations. We also compare our results with a few experimental facts reported in the literature and propose new experiments for testing some of our new quantitative predictions.

23. Geomagnetic field intensity may be a cue for the regulation of insect migration

15 August 2019 | Biorxiv link | Write review

The geomagnetic field (GMF) intensity can help animal migrants to determine position during their migration. However, its potential roles in mediating other migration-related phenotypes remain mostly unknown. Here, by simulating the GMF total intensity of two points (GMF50T vs. GMF45T) in the migration route of a nocturnal insect migrant, brown planthopper Nilaparvata lugens, we investigated their magnetic responses of three crucial migration-involved performance including wing dimorphism, flight capacity and positive phototaxis to only a ~5 T change in field intensity after one generation exposure. Our results showed that all the three phenotypes of N. lugens could respond to the small changes in field intensity between the mimic northern vs. southern region (GMF50T vs. GMF45T) in a way potentially benefitting their south-to-north expanding and securing a thriving population. Consistent magnetic response patterns of phototaxis-related Drosophila-like cryptochrome 1 (Cry1) and two primary energy substances during flight, including triglyceride and trehalose, were also found. Our findings indicate the potential importance of GMF intensity in the regulation of insect migration and highlight the unique role of magnetoreception in helping insect adapt to the environment.

24. Survival analysis, the infinite Gaussian mixture model, FDG-PET and non-imaging data in the prediction of progression from mild cognitive impairment

15 August 2019 | Arxiv link | Write review

We present a method to discover interesting brain regions in [18F] fluorodeoxyglucose positron emission tomography (PET) scans, showing also the benefits when PET scans are in combined use with non-imaging variables. The discriminative brain regions facilitate a better understanding of Alzheimer's disease (AD) progression, and they can also be used for predicting conversion from mild cognitive impairment (MCI) to AD. A survival analysis(Cox regression) and infinite Gaussian mixture model (IGMM) are introduced to identify the informative brain regions, which can be further used to make a prediction of conversion (in two years) from MCI to AD using only the baseline PET scan. Further, the predictive accuracy can be enhanced when non-imaging variables are used together with identified informative brain voxels. The results suggest that PET scan imaging data is more predictive than other non-imaging data, revealing even better performance when both imaging and non-imaging data are combined.

25. Selection for altruistic defense in structured populations

14 August 2019 | Biorxiv link | Write review

We model natural selection for or against an altruistic defense allele of a host (or prey) against a parasite (or predator). The populations are structured in demes and we specify rates for birth, death, and migration events of single individuals.The defense behavior has a fitness cost for the actor and locally reduces parasite growth rates. In a previous study (Hutzenthaler, Jordan, Metzler, 2015), we analytically derived a criterion for fixation or extinction of altruists in the limit of large populations, many demes, weak selection and slow migration. Here, we use two simulation approaches to analyze the model in relaxed settings. We confirm that the criterion still holds for settings with finitely many demes with various migration patterns if populations are large and the ecological interactions are fast compared to evolutionary processes. For smaller populations with no complete separation of evolutionary and ecological time scales, the value of the shift between fixation and extinction changes, but the qualitative insights remain valid. The key mechanism of providing a benefit of altruism is randomness of reproduction and death events leading to differences in population sizes between demes. Randomness, which is more pronounced for small populations, improves the conditions for fixation of the altruistic allele. Furthermore, as suggested by the previous asymptotic results, we find no significant effect of the migration rate and conclude that the amount of gene flow under which the evolution of altruism is favored may not be as limited as suggested by previous studies.

26. Multi-locus data distinguishes between population growth and multiple merger coalescents

14 August 2019 | Arxiv link | Write review

We introduce a low dimensional function of the site frequency spectrum that is tailor-made for distinguishing coalescent models with multiple mergers from Kingman coalescent models with population growth, and use this function to construct a hypothesis test between these model classes. The null and alternative sampling distributions of the statistic are intractable, but its low dimensionality renders them amenable to Monte Carlo estimation. We construct kernel density estimates of the sampling distributions based on simulated data, and show that the resulting hypothesis test dramatically improves on the statistical power of a current state-of-the-art method. A key reason for this improvement is the use of multi-locus data, in particular averaging observed site frequency spectra across unlinked loci to reduce sampling variance. We also demonstrate the robustness of our method to nuisance and tuning parameters. Finally we show that the same kernel density estimates can be used to conduct parameter estimation, and argue that our method is readily generalisable for applications in model selection, parameter inference and experimental design.

27. In situ activation and heterologous production of a cryptic lantibiotic from a plant-ant derived Saccharopolyspora species

14 August 2019 | Biorxiv link | Write review

Most clinical antibiotics are derived from actinomycete natural products (NPs) discovered at least 60 years ago. Repeated rediscovery of known compounds led the pharmaceutical industry to largely discard microbial NPs as a source of new chemical diversity but advances in genome sequencing revealed that these organisms have the potential to make many more NPs than previously thought. Approaches to unlock NP biosynthesis by genetic manipulation of the strain, by the application of chemical genetics, or by microbial co-cultivation have resulted in the identification of new antibacterial compounds. Concomitantly, intensive exploration of coevolved ecological niches, such as insect-microbe defensive symbioses, has revealed these to be a rich source of chemical novelty. Here we report the novel lanthipeptide antibiotic kyamicin generated through the activation of a cryptic biosynthetic gene cluster identified by genome mining Saccharopolyspora species found in the obligate domatia-dwelling ant Tetraponera penzigi of the ant plant Vachellia drepanolobium. Heterologous production and purification of kyamicin allowed its structural characterisation and bioactivity determination. Our activation strategy was also successful for the expression of lantibiotics from other genera, paving the way for a synthetic heterologous expression platform for the discovery of lanthipeptides that are not detected under laboratory conditions or that are new to nature.

28. Distributions of covariances as a window into the operational regime of neuronal networks

14 August 2019 | Arxiv link | Write review

Massively parallel recordings of spiking activity in cortical networks show that covariances vary widely across pairs of neurons. Their low average is well understood, but an explanation for the wide distribution in relation to the static (quenched) disorder of the connectivity in recurrent random networks was so far elusive. We here derive a finite-size mean-field theory that reduces a disordered to a highly symmetric network with fluctuating auxiliary fields. The exposed analytical relation between the statistics of connections and the statistics of pairwise covariances shows that both, average and dispersion of the latter, diverge at a critical coupling. At this point, a network of nonlinear units transits from regular to chaotic dynamics. Applying these results to recordings from the mammalian brain suggests its operation close to this edge of criticality.

29. Development of structure-function coupling in human brain networks during youth

13 August 2019 | Biorxiv link | Write review

The protracted development of structural and functional brain connectivity within distributed association networks coincides with improvements in higher-order cognitive processes such as working memory. However, it remains unclear how white matter architecture develops during youth to directly support coordinated neural activity. Here, we characterize the development of structure-function coupling using diffusion-weighted imaging and n-back fMRI data in a sample of 727 individuals (ages 8-23 years). We found that spatial variability in structure-function coupling aligned with cortical hierarchies of functional specialization and evolutionary expansion. Furthermore, hierarchy-dependent age effects on structure-function coupling localized to transmodal cortex in both cross-sectional data and a subset of participants with longitudinal data (n=294). Moreover, structure-function coupling in rostrolateral prefrontal cortex was associated with executive performance, and partially mediated age-related improvements in executive function. Together, these findings delineate a critical dimension of adolescent brain development, whereby the coupling between structural and functional connectivity remodels to support functional specialization and cognition.

30. Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo

13 August 2019 | Arxiv link | Write review

We present a sequential Monte Carlo algorithm for Markov chain trajectories with proposals constructed in reverse time, which is advantageous when paths are conditioned to end in a rare set. The reverse time proposal distribution is constructed by approximating the ratio of Green's functions in Nagasawa's formula. Conditioning arguments can be used to interpret these ratios as low-dimensional conditional sampling distributions of some coordinates of the process given the others. Hence the difficulty in designing SMC proposals in high dimension is greatly reduced. We illustrate our method on estimating an overflow probability in a queueing model, the probability that a diffusion follows a narrowing corridor, and the initial location of an infection in an epidemic model on a network.